Find Your Dream Career

Title: GenAI Engineer Job Summary We are looking for a GenAI Engineer to design, develop, and integrate Generative AI solutions into applications and business processes. The ideal candidate should have a basic understanding of Python, Large Language Models (LLMs), prompt engineering, RAG, APIs, and machine learning concepts . Key Responsibilities: Develop applications using Generative AI and Large Language Models (LLMs) . Build and test prompt engineering techniques for different use cases. Develop RAG (Retrieval-Augmented Generation) applications using company documents and knowledge bases. Integrate AI models through APIs such as OpenAI or other LLM providers. Work with vector databases for storing and searching document embeddings. Develop Python-based AI applications and automation workflows. Evaluate LLM responses for accuracy, relevance, and quality. Perform data preprocessing, document processing, and text extraction. Work with AI frameworks and libraries such as LangChain, LlamaIndex, or similar tools . Collaborate with software engineers, data scientists, and product teams to deploy AI solutions. Stay updated with new developments in Generative AI, LLMs, and AI tools . Required Skills Python programming Basic Machine Learning / Deep Learning knowledge Understanding of Generative AI and LLMs Prompt Engineering Understanding of RAG Experience with REST APIs Basic knowledge of embeddings and vector databases Familiarity with tools such as: OpenAI / Azure OpenAI LangChain LlamaIndex FAISS, Chroma, Pinecone, or similar vector databases Basic knowledge of Git and GitHub Good problem-solving and communication skills Good to Have Knowledge of AWS, Azure, or Google Cloud Experience with Docker Knowledge of SQL and databases Familiarity with AI agents and tool calling Basic understanding of model evaluation and AI safety Experience deploying Python applications using FastAPI or similar frameworks Education & Experience Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. 5+ years of experience in software development, AI/ML, or Generative AI.

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets. Our challenge We are seeking a skilled GenAI Engineer with strong experience in Python, LangChain, and LangGraph to design, develop, and deploy intelligent AI applications and agentic workflows. The ideal candidate will have hands-on experience building production-ready solutions using large language models, retrieval-augmented generation, tool-calling, and multi-agent systems. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Charlotte, NC is $90k - $105k/year & benefits (see below). The Role Responsibilities: Design, develop, and deploy generative AI applications using large language models. Build LLM-powered workflows, assistants, chatbots, and automation solutions using LangChain and LangGraph . Develop agentic systems with capabilities such as:Tool and function calling Planning and reasoning Memory management Workflow orchestration Human-in-the-loop approvals Multi-agent collaboration Implement retrieval-augmented generation (RAG) pipelines using document processing, embeddings, vector databases, and semantic search. Integrate LLM applications with APIs, enterprise systems, databases, and third-party services. Develop robust prompts, structured outputs, evaluation frameworks, and guardrails. Optimize applications for accuracy, latency, scalability, cost, and reliability. Build and maintain reusable Python services, libraries, and APIs. Conduct testing and evaluation of LLM outputs, including relevance, factuality, safety, and consistency. Monitor production AI systems and troubleshoot performance or quality issues. Requirements: Strong professional experience developing applications using Python . Hands-on experience with LangChain and LangGraph . Solid understanding of:Large language models and transformer-based architectures Prompt engineering Embeddings and vector search Retrieval-augmented generation AI agents and workflow orchestration Function calling and structured data extraction Experience working with LLM providers such as OpenAI, Anthropic, Google Vertex AI/Gemini, or Azure OpenAI. Experience with REST APIs, microservices, and backend application development. Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or pgvector. Experience with Angular. We offer: A highly competitive compensation and benefits package. A multinational organization with 58 offices in 22 countries and the possibility to work abroad. 10 days of paid annual leave (plus sick leave and national holidays). Maternity & paternity leave plans. A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region). Retirement savings plans. A higher education certification policy. Commuter benefits (varies by region). Extensive training opportunities, focused on skills, substantive knowledge, and personal development. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms. A flat and approachable organization. A truly diverse, fun-loving, and global work culture. S YNECHRON'S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative 'Same Difference' is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Responsibilities Team Introduction: We build the next-generation unified Agent system for TikTok's global e-Commerce customer service — running in 30+ languages across one of the largest e-Commerce surfaces on the internet. Our north star is a self-evolving Agent: post-training, harness, memory / context engineering, tools, and evaluation form one closed loop, and every served conversation becomes the next iteration's training / eval / retrieval / skill-induction signal. This loop is already running in production — cases are mined, root-caused, turned into constrained candidates, replayed against frozen regression sets, and shipped behind guardrails. Two things make this team different from most "LLM application" work: We build the agent runtime itself — Codex / Claude-Code-class — not prompts on top of a vendor API. Evaluation and experimentation are first-class systems, not an afterthought. A self-improving loop optimizes whatever signal you give it, so the hardest and most valuable engineering here is making the judgment trustworthy — not just making the model change. By combining generative recommendation, large recommendation models, multimodal representation learning, and cross-domain value modeling, the team works on some of the most important algorithmic problems in live commerce. Our goal is to improve user experience, optimize ecosystem efficiency, and drive sustainable business growth for TikTok Shop across global markets. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: Agent runtime (harness / agent loop). Orchestrate skills, tools, and context; implement loop control & intervention, progressive disclosure, and behavior-level guardrails. Build the production safety layer — pre-flight budgets and timeout truncation, serve-time gates, shadow / swap-in answer delivery, and safe fallback paths. Context & memory for long multi-turn agents. Agentic memory (structured note-taking), context compaction / summarization, context editing / observation masking, and just-in-time (retrieve-then-load) retrieval. Treat context as an evolving, itemized playbook — with structured diffs and a deterministic curator — rather than an ever-growing prompt. Post-training & the data flywheel. SFT / DPO / RL to internalize rules into weights (so the prompt gets shorter, not longer), plus distillation to smaller serving models. Turn served conversations into training / eval / retrieval signals. Tools, Skills, and MCP. Tools-as-APIs, connectors, skill / tool search for large inventories, and skill-library governance — description conflicts, trigger evals, cross-skill mis-fire matrices, and on-demand loading instead of dumping every definition into context. Evaluation you can bet a launch on. LLM-as-judge with human-agreement calibration; statistical rigor — paired comparison, confidence intervals, repeated sampling, pass^k; held-out and time-rolling eval splits with overfitting alarms; cascaded scoring and cross-family judge panels to make evaluation affordable at scale. The self-evolving loop. Case mining → automatic root-cause → constrained candidate generation → replay verification against frozen regression sets → canary → flywheel. Build the plumbing that makes it auditable: candidate registry with exact runtime read-back, change lineage, and an archive of rejected candidates you can sample from next round. Online experimentation & causal readout. Shadow / canary / A-B, non-inferiority gates, traffic-split health, metric definitions that survive scrutiny, and off-policy counterfactual evaluation where live A/B isn't possible. Qualifications Minimum Qualification(s): Individuals who are completing or have recently completed a Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline Strong Python plus one of C++ / Go / Rust / Java Solid ML / DL / NLP fundamentals, with genuine hands-on experience with LLMs or agents (coursework, research, internship, competition, open-source, or a serious side project) Basic statistical literacy — you can compute a confidence interval, explain what a p-value does and doesn't mean, and tell the difference between "the number went up" and "the system got better" Able to read a paper or an engineering blog and turn it into working code Preferred Qualification(s) Have built the runtime, not just called an API — even at research / hobby / competition scale: your own agent loop / harness, a memory / context-management system, a RAG or tool-use agent, or a fine-tuned / post-trained model Hands-on experience in any one of the following — depth in one is enough, breadth welcome: Post-training: SFT / DPO / RLHF / RLAIF / RLVR, reward modeling, reward hacking and how to defend against it Agent systems: harness, context engineering, MCP / Skills, sub-agents, tool search Evaluation & experimentation: LLM-as-judge and judge calibration, pass^k, regression suites, A/B and non-inferiority testing, off-policy evaluation Self-improving / evolutionary systems: evolutionary program search, candidate archives and parent sampling, automatic prompt / context optimization, multi-objective (Pareto) selection and credit assignment Inference & serving: vLLM / TensorRT-LLM, MoE, KV / prompt caching, and the cost engineering that comes with it Multilingual NLP Publications (for PhD), strong competition results (ACM-ICPC / Kaggle / ML competitions), or notable open-source contributions Taste for the honest number. We'd rather hire someone who says "this result isn't significant yet" than someone who ships a green dashboard. If you've ever killed your own experiment because the evidence didn't hold up, tell us about it. e-Commerce or multilingual experience is a plus, not required Job Information 【For Pay Transparency】Compensation Description (Annually) The base salary range for this position in the selected city is $121600 - $243200 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure). The Company reserves the right to modify or change these benefits programs at any time, with or without notice. For Los Angeles County (unincorporated) Candidates: Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and Exercising sound judgment. About TikTok TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo. Why Join Us Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us. Diversity & Inclusion TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok Accommodation TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request

Company Qualcomm Technologies, Inc. Job Area Engineering Group, Engineering Group > Modem Technologies Software General Summary This position is not eligible for Qualcomm immigration sponsorship.*** We are seeking an experienced Machine Learning Engineer specializing in Agentic AI to join our Core Enterprise AI team. The ideal candidate will design, develop, and deploy next-generation AI systems powered by Large Language Models (LLMs), Agentic AI, Hybrid AI architectures, Retrieval-Augmented Generation (RAG), and autonomous intelligent agents . This role focuses on building enterprise-grade AI solutions capable of reasoning, planning, tool usage, workflow orchestration, and autonomous task execution. Key Responsibilities Design and implement Agentic AI systems capable of autonomous reasoning, planning, tool usage, and multi-step execution to solve complex enterprise problems. Build and optimize RAG, Hybrid AI, and knowledge-grounded architectures that augment LLMs with enterprise data, external tools, and domain-specific context. Develop and advance self-improving AI agents leveraging feedback loops, reflection, reinforcement learning techniques, automated evaluations, memory systems, and continuous learning frameworks. Research, develop, and apply LLM post-training techniques, including supervised fine-tuning (SFT), preference optimization, reinforcement learning, distillation, and domain adaptation to improve model performance for enterprise use cases. Create robust evaluation, benchmarking, observability, and safety frameworks for measuring agent quality, reliability, efficiency, and business impact. Build and maintain multi-agent systems and orchestration frameworks that enable collaborative agent workflows and intelligent task automation. Collaborate with cross-functional teams to identify high-value opportunities and deliver scalable AI solutions that drive measurable business outcomes. Stay at the forefront of advancements in Agentic AI, reasoning models, post-training, model routing, autonomous agents, and enterprise AI architectures, bringing innovative solutions into production. Minimum Qualifications Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field. Preferred Qualifications Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers) Knowledge of prompt engineering and chain-of-thought techniques Experience with containerization and microservices architecture Background in Reinforcement Learning Contributions to open-source AI projects Experience with ML ops and model deployment pipelines Skills And Competencies Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow) Practical experience with LLM deployments and fine-tuning Experience with vector databases and embedding models Familiarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure) Strong understanding of RAG architectures and implementation Strong problem-solving and analytical skills Excellent communication and collaboration abilities Experience with agile development methodologies Ability to balance multiple projects and priorities Strong focus on code quality and best practices Understanding of AI ethics and responsible AI development Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. Pay Range And Other Compensation & Benefits $114,500.00 - $171,700.00 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link. If you would like more information about this role, please contact Qualcomm Careers.

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title Applied AI Engineer Location: 100% Remote (Continental United States) Position Type: Full-time, Direct W2 Salary Range: $130,000–$180,000 Annually (based on experience) Experience Required: 10+ Years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary Bright Vision Technologies is seeking a highly experienced Applied AI Engineer with 10+ years of experience in Artificial Intelligence, Machine Learning, and Deep Learning to design, develop, and deploy enterprise-scale AI solutions. The ideal candidate will possess deep expertise in Python, PyTorch or JAX, Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, and MLOps , with a proven track record of taking AI models from research to production. This role requires strong technical leadership, hands-on development, and the ability to architect scalable, secure, and high-performance AI systems. Key Responsibilities Design, develop, and deploy production-grade AI and machine learning solutions that address complex business challenges. Architect scalable training, inference, and MLOps pipelines for enterprise AI applications. Develop, fine-tune, evaluate, and optimize Large Language Models (LLMs) , deep learning models, and multimodal AI systems. Build AI applications leveraging Retrieval-Augmented Generation (RAG) , vector databases, embeddings, prompt engineering, and agentic AI frameworks. Design and implement machine learning pipelines for NLP, Computer Vision, recommendation systems, and predictive analytics. Optimize model performance, latency, scalability, and infrastructure utilization across cloud and distributed computing environments. Collaborate with data scientists, software engineers, product managers, and business stakeholders to deliver production-ready AI solutions. Establish best practices for model evaluation, Responsible AI, governance, security, monitoring, and lifecycle management. Mentor junior AI engineers and contribute to technical leadership, architecture reviews, and engineering best practices. Evaluate emerging AI technologies, foundation models, and frameworks to drive continuous innovation. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline. 10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Applied AI. Expert-level programming skills in Python with extensive experience using PyTorch, JAX, or TensorFlow . Proven experience developing and deploying Large Language Models (LLMs) , NLP, Computer Vision, and deep learning applications in production. Strong knowledge of distributed training, GPU optimization, model serving, and production ML deployment. Hands-on experience with MLOps , CI/CD pipelines, model monitoring, feature engineering, and automated ML workflows. Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) for AI workloads. Strong understanding of machine learning algorithms, statistics, model evaluation, experimentation, and optimization techniques. Excellent problem-solving, communication, collaboration, and technical leadership skills. Preferred Qualifications Experience with LLM fine-tuning , Retrieval-Augmented Generation (RAG) , agentic AI , multimodal AI , and vector databases such as Pinecone, Weaviate, Milvus, or FAISS . Hands-on experience with AI orchestration frameworks such as LangChain , LlamaIndex , LangGraph , or similar technologies. Experience deploying AI applications using Kubernetes, Docker, Ray, or distributed inference frameworks. Publications in AI/ML conferences, open-source contributions, patents, or recognized technical leadership in the AI community. Knowledge of Responsible AI, AI governance, model security, fairness, explainability, and regulatory compliance. Ph.D. or Master's degree with a specialization in Artificial Intelligence, Machine Learning, Computer Vision, or Natural Language Processing. Interested in this opportunity? Apply today for immediate consideration! Email your updated resume: jaya@bvteck.com Call or Text: (908) 505-3545 Learn More Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Senior Machine Learning Engineer Remote | Direct Hire $160K – $175K Base We are seeking a hands-on Senior Machine Learning Engineer to architect, build, and own end-to-end production ML systems for a growing enterprise SaaS platform. This role focuses on developing intelligent systems that classify, normalize, and enrich large volumes of complex business and transactional data using machine learning, NLP, and modern AI technologies. Responsibilities Architect and develop end-to-end production ML systems. Build classification, categorization, entity-matching, and data-normalization models. Develop scalable ML pipelines for training, inference, and deployment. Implement confidence scoring, model monitoring, drift detection, and retraining. Leverage Python, PyTorch, NLP, embeddings, and LLMs where appropriate. Build reliable MLOps infrastructure supporting multiple enterprise customers. Own technical decisions and collaborate with engineering, data science, and product teams. Requirements 6+ years of ML Engineering, Applied AI, or related experience. Strong Python and experience with PyTorch, TensorFlow, or scikit-learn. Proven end-to-end ownership of production ML systems. Experience with classification, NLP, entity matching, or similar modeling challenges. Strong MLOps experience, including deployment, monitoring, and retraining. Experience with AWS, SageMaker, Docker, Kubernetes, or comparable cloud infrastructure. Excellent problem-solving, architecture, and communication skills. Ideal Candidate: An engineer who can independently design, build, deploy, monitor, and improve scalable machine learning systems - not simply train models or maintain existing infrastructure.

Sony Pictures Entertainment is seeking a talented data engineer to join the Insights, Strategy and Analytics (ISA) organization. The ISA team focuses on enhancing analytical capabilities and infrastructure for internal stakeholders across television production, distribution, and marketing. As the world's largest independent studio, Sony Pictures Television produces original content for streaming and linear networks globally, including popular series across various genres. Our series – from dramas like PLURIBUS, THE NIGHT AGENT, THE LAST OF US, and THE BOYS, to comedies like TWISTED METAL and COBRA KAI, to unscripted series like JEOPARDY!, WHEEL OF FORTUNE, and AMERICAN IDOL – are beloved by our fans and customers worldwide. The Data Engineer II designs and builds reliable, scalable ELT pipelines that power analytics, reporting, and AI/ML applications across Sony Pictures Entertainment. Ideal candidates have prior experience supporting data platforms, analytics, or business intelligence initiatives within a film or television studio, streaming platform, broadcast network, or similarly scaled media company. This role contributes to fast-paced, business-facing analytics initiatives, delivering data products and analytical capabilities that support strategic decision-making across the studio. Key Responsibilities Analytics Engineering: Translate complex business requests into robust data models, business metrics, and semantic layers using dbt and SQL. Apply analytics engineering best practices to ensure maintainability, reliability, and performance. Data Engineering: Support the ingestion of new sources into SPE's Snowflake data platform, working closely with central IT and cloud operations teams to define ingestion requirements and validate that pipelines meet business needs and adhere to SPE's data governance and security policies. Cross-Functional Product Delivery: Partner closely with product managers, strategic analysts, data scientists, data visualization teams, and business stakeholders to deliver impactful tools. Collaborate across disciplines to understand business requirements, harmonize data from disparate systems, and create ready-to-use datasets that enable reporting, advanced analytics, and decision-making. "One Team" Mindset: Contribute to a high-performance team, collaborating openly with peers to create a team culture of ownership, accountability, and continuous improvement. Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Business Analytics, or related fields; advanced degrees are a plus. 5+ years in analytics engineering, data engineering, or a related technical role in a production environment. Experience working with data supporting television, film, streaming, advertising-supported video (AVOD), FAST channels, content distribution, audience analytics, or media strategy. Familiarity with business entities, metrics, and datasets common to a television production and distribution studio, including content and title metadata, audience measurement, ratings, and content performance data, talent, production, licensing, and distribution datasets. Experience working with industry data providers such as IMDb, Gracenote, Luminate, Nielsen, or similar sources is highly desirable. Advanced SQL and Python skills. Experience building transformation pipelines in dbt is strongly preferred. Proficiency with modern cloud data platforms (e.g., Snowflake, GCP/BigQuery, AWS/Redshift) and with pipeline orchestration tools. Familiarity with CI/CD workflows, version control, and automated testing frameworks to meet data quality standards. Exposure to generative AI technologies and practical interest in applying AI-driven approaches to data engineering, data quality, metadata management, and analytics workflows. Strong problem-solving skills, attention to detail, and the ability to communicate effectively with both technical and non-technical stakeholders. The anticipated base salary for this position is $1250K to $160K. This role may also qualify for annual incentive and/or comprehensive benefits. The actual base salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location of the position. Sony Pictures Entertainment is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, age, sexual orientation, gender identity, or other protected characteristics. SPE will consider qualified applicants with arrest or conviction records in accordance with applicable law. To request an accommodation for purposes of participating in the hiring process, you may contact us at SPE_Accommodation_Assistance@spe.sony.com.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI is seeking a Senior Analytics Engineer to lead the design and delivery of trusted data products for Corporate FP&A, Accounting, Program Finance, GTM, and Strategic Finance. You will independently shape analytical solutions, establish shared standards, and turn business priorities into AI-enabled decision support on our Databricks platform. This senior individual contributor role combines hands-on engineering with cross-functional influence and mentorship to expand Finance's impact. What you'll do: Shape the analytics roadmap with Finance and GTM leaders, prioritizing high-impact products and resolving competing requirements. Build governed datasets and semantic models that support reporting, planning, scenario analysis, and strategic decisions. Set modeling and metric standards across domains, exercising judgment on architecture, quality, and maintainability. Develop conversational analytics and AI-enabled workflows, including Databricks Genie, grounded in trusted business context. Use AI coding assistants to accelerate delivery and explore new capabilities while maintaining rigorous validation and quality. Own business-facing reconciliation and acceptance, partnering with data engineering on reliable delivery. Mentor engineers and Finance partners, strengthening technical practices and self-service capabilities. Required qualifications: Substantial experience in analytics engineering, BI engineering, or financial data modeling, with advanced SQL and a record of delivering production data products. Demonstrated ability to lead ambiguous, cross-functional work from problem definition through adoption. Proficiency with AI coding assistants and sound judgment when reviewing generated work. Practical experience with AI-assisted analytics, ideally Databricks Genie; adjacent Snowflake Cortex or comparable experience is welcome. Sound architectural judgment, disciplined development practices, and experience mentoring others and influencing senior stakeholders. Preferred qualifications: Experience with Databricks, Python, semantic layers, or AI application development. Experience supporting FP&A, GTM, Strategic Finance, Accounting, or Program Finance. Familiarity with enterprise planning, financial controls, or high-growth business environments. $120,000 - $190,000 a year #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Description Full-Time | Remote or Draper, UT Campus (Hybrid) Join Us in Transforming Healthcare Education At Joyce University, the work we do goes beyond technology—it helps move the University forward and supports our mission of preparing people to serve as competent professionals, advance their careers, and pursue lifelong learning. We are seeking an Analytics Engineer to help build the trusted data foundation that enables reporting, insights, and data-driven decision-making across Joyce University. In this role, you will transform data from multiple sources into clean, reliable, analytics-ready datasets and develop the models, metrics, and tools that help teams understand and use data effectively. You will work closely with teams across the University to understand their reporting and analytical needs and translate those needs into scalable data models, standardized metrics, and meaningful insights. Your work will help support self-service analytics, institutional reporting, strategic planning, and everyday decision-making. This is an opportunity to play an important role in helping a growing university turn data into insights that advance healthcare education and support the student journey. What You'll Do Data Modeling & Analytics Engineering Design, build, and maintain analytics-ready data models that support reporting, dashboards, and advanced analysis Transform raw data from multiple sources into clean, reliable, and well-documented datasets Translate business requirements into technical data models, metrics, and KPIs Develop and maintain semantic layers, standardized metrics definitions, and documentation Optimize data models for performance, scalability, and long-term maintainability Contribute to analytics engineering standards, tooling, and data governance practices Data Collection & Processing Extract, transform, and load (ETL) data from diverse data sources and systems Build and maintain automated pipelines, scripts, and workflows for data ingestion and transformation Partner closely with data engineers to define data pipelines, schemas, and best practices Data Analysis & Interpretation Perform exploratory data analysis to identify trends, patterns, and anomalies Apply statistical, analytical, and modeling techniques to generate actionable insights Data Visualization & Reporting Design and deliver interactive dashboards, and reports for stakeholders Communicate insights clearly to both technical and non-technical audiences Enable self-service analytics by supporting business users with trusted datasets and metrics Data Quality & Reliability Ensure data quality, consistency, and reliability through testing, validation, and monitoring Identify, investigate, and resolve data discrepancies and quality issues Implement data quality controls to support accurate and trustworthy analytics What We Offer At Joyce, we believe great work starts with an environment where people feel trusted, supported, and connected to a meaningful purpose. Self-directed paid time off 12 paid holidays Medical, dental, and vision insurance Employer-paid short-term and long-term disability coverage 401(k) retirement plan Professional development opportunities Continuing education opportunities A mission-driven environment focused on healthcare education and student success The flexibility to work fully remote or in a hybrid arrangement from our Draper, Utah campus Requirements What You'll Bring We welcome candidates who bring strong analytical and technical skills, curiosity, and a commitment to making data useful and accessible. You should enjoy connecting business questions with data solutions and be comfortable working independently while partnering with technical and non-technical colleagues across the University. Required Qualifications Bachelor's degree in a quantitative field or equivalent practical experience Strong SQL skills and experience working with relational data models Experience with data transformation tools, such as dbt or similar frameworks Experience transforming raw data into clean, reliable, and well-documented datasets Familiarity with modern data warehouses and ELT/ETL pipelines Solid understanding of data modeling, metrics design, and data quality best practices Experience translating business requirements into scalable analytical solutions Strong analytical thinking, attention to detail, and communication skills What You'll Love About Joyce At Joyce, we believe meaningful work and a great employee experience go hand in hand. Here, you'll find a community that cares about the work we do, the people we serve, and the people we work alongside. Purposeful Work – Your work helps turn data into insights that support the people, systems, and decisions that move healthcare education forward and ultimately make a difference for our students. A Culture of Care – We believe in treating people with warmth, respect, and genuine care. Unreasonable Hospitality is the floor, not the ceiling. Flexibility & Trust – We trust our people to do great work. This role offers the flexibility to work fully remote or in a hybrid arrangement from our Draper, Utah campus. Learning & Growth – We believe learning never stops. You'll have opportunities to build your skills, pursue professional development, and grow alongside a University that is continuing to evolve. People Who Care – You'll work with talented, collaborative colleagues who are committed to helping one another succeed and creating a positive experience for our students and each other. A Growing University – Joyce is a place where your ideas can make an impact. As we grow and innovate, you'll have opportunities to help shape how we work and build what comes next. Work That Matters – Every interaction moves the student forward. No matter your role, the work you do at Joyce contributes to preparing the next generation of healthcare professionals. About Joyce University Joyce University of Nursing & Health Sciences is committed to preparing people to serve as competent professionals, advance their careers, and pursue lifelong learning. Founded in 1979, Joyce has grown into a leading healthcare education institution with pre- and post-licensure programs designed to prepare students for meaningful careers in healthcare. We are a community that values Service, Learning, Integrity, Caring, and Excellence , and we believe every interaction has the opportunity to move the student journey forward.

Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America. We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well-being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands. About Clarus Clarus, a Doubtless company, is a pioneering pet health technology company transforming the future of pet healthcare. We develop connected solutions across the pet health landscape, helping veterinary teams and pet owners make more informed care and financial decisions. Together, we are reducing complexity and helping more pets receive the care they need. About The Role Clarus is seeking an experienced Analytics Engineer to join the Analytics team. This individual will own the analytics engineering process and serve as the technical bridge between Data Engineering and Analytics delivery. They will build, expand, and optimize Clarus's analytics architecture and pipelines, improving how data flows from diverse sources to downstream analytics solutions. In this role, you will lead high-impact data product and solutions initiatives from ambiguous problem definition through technical design, implementation, rollout, and adoption. You will transform raw and curated data into reliable, analytics-ready models and consistent business metrics using dbt, SQL, Python, and Databricks, while establishing a scalable architecture and strong engineering practices. The ideal candidate is a seasoned analytics engineer with strong data-wrangling skills and a passion for building and optimizing scalable analytics systems. They are self-directed, comfortable supporting multiple projects, systems, and products, and able to set technical direction while remaining deeply hands-on. What You'll Do Own analytics engineering work, including its roadmap, priorities, standards, and operating practices. Design and evolve analytics architecture, with clear responsibilities and quality expectations across bronze, silver, and gold data layers. Build, maintain, and optimize dbt models that transform source data into curated, reusable, analytics-ready datasets. Write and optimize advanced SQL, and use Python for data transformation, validation, automation, and complex processing where appropriate. Develop dimensional and business-oriented data models that support dashboards, self-service analysis, operational reporting, and data products. Establish and document shared KPI definitions, calculation logic, data contracts, ownership, and authoritative sources. Implement automated tests, source freshness checks, documentation, lineage, and monitoring to make data quality visible and dependable. Establish disciplined development practices, including Git-based version control, code review, CI/CD, and controlled promotion across environments. Partner with Data Engineering on ingestion, source schemas, platform performance, and reliable handoffs between foundational and analytical data layers. Partner with analysts, BI developers, and business stakeholders to translate requirements into scalable models rather than one-off reporting logic. Improve Databricks performance and cost efficiency through thoughtful table design, incremental processing, query optimization, and compute usage. Lead data-quality investigations, root-cause analysis, remediation, and communication when critical analytics assets do not meet expectations. Strengthen data governance by applying appropriate access controls, handling sensitive data responsibly, and supporting consistent ownership and stewardship. Migrate duplicated spreadsheet, dashboard, and ad hoc query logic into governed, tested, and reusable dbt models. Design resilient models that support historical analysis, changing source systems, incremental loads, and evolving business definitions. Create clear technical documentation, modeling conventions, and enablement materials that drive adoption of trusted data assets. Raise analytics engineering capability across the team through design reviews, reusable patterns, thoughtful feedback, and hands-on mentorship. What You Bring Bachelor's degree or higher in computer science, data engineering, analytics, information systems, mathematics, or a related discipline, or equivalent professional experience. A strong record of success leading complex analytics engineering, data engineering, business intelligence engineering, or closely related initiatives. Experience in animal health, veterinary services, pet insurance, SaaS, fintech, or health technology is a plus. 8+ years of relevant data and analytics experience, including senior-level ownership of production analytics data models and standards. Advanced SQL skills and demonstrated experience designing, debugging, and optimizing complex transformations. Deep, hands-on dbt experience, including scalable model architecture, testing, incremental models, snapshots, documentation, macros, packages, and production deployment workflows. Strong Databricks experience, including Delta Lake, Spark SQL, Workflows or Jobs, Unity Catalog, and performance management / tuning. Demonstrated skill operating medallion architectures and lakehouse data models across bronze, silver, and gold layers. Strong Python skills for data processing, testing, validation, automation, and engineering utilities. Strong understanding of dimensional modeling, warehouse and lakehouse design, semantic layers, slowly changing dimensions, and metric governance. Experience with modern engineering practices, including Git, CI/CD, code review, automated testing, orchestration, and environment management. Ability to translate ambiguous business needs into clear technical designs and communicate effectively with senior leaders and non-technical stakeholders. What Will Help You Succeed You are intellectually curious, resourceful, and motivated to understand how the business works. You take initiative, identify needs early, and you are comfortable operating in an evolving, high-growth environment. You can move easily between hands-on analytics engineering, and stakeholder conversations. You can manage production data deliverables while continuing to improve the underlying processes. You build trust by producing reliable data products, communicating clearly, and following through on commitments. LOCATION This is a remote U.S. position aligned to Eastern or Central Time business hours. U.S. travel may be required. Compensation Chicago/Boston Base pay range: $123,774 – $154,718 per year NYC Base pay range: $135,026 - $168,784 per year Miami Base pay range: $118,148 - $147,686 Nationwide Base pay range: $112,522 - 140,653 per year This is the range we reasonably expect to pay at hire. Placement within the range depends on job-related factors such as experience, skills, and certifications. This position is eligible for an annual bonus. Base pay is one part of a total rewards package that includes the benefits listed below. All of our jobs come with great benefits including healthcare, parental leave and opportunities for career advancements. Some offerings are dependent upon the location of where you work and can include the following: Comprehensive full medical, dental and vision Insurance Basic Life Insurance at no cost to the employee Company paid short-term and long-term disability 12 weeks of 100% paid Parental Leave Health Savings Account (HSA) Flexible Spending Accounts (FSA) Retirement savings plan Personal Paid Time Off Paid holidays and company-wide Wellness Day off Paid time off to volunteer at nonprofit organizations Pet friendly office environment Commuter Benefits Group Pet Insurance On the job training and skills development Employee Assistance Program (EAP) Interview Technology Notice Please note that phone and video interviews or screenings may be recorded and transcribed using interview technology to support our recruitment process. By continuing with the interview, you consent to this use. Text Messaging Notice If you provide a mobile phone number, you may receive job-related communications via text message. Message and data rates may apply. You may opt out of text communications at any time by replying "STOP."

Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America. We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well-being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands. About Clarus Clarus, a Doubtless company, is a pioneering pet health technology company transforming the future of pet healthcare. We develop connected solutions across the pet health landscape, helping veterinary teams and pet owners make more informed care and financial decisions. Together, we are reducing complexity and helping more pets receive the care they need. About The Role Clarus is seeking an experienced Analytics Engineer to join the Analytics team. This individual will own the analytics engineering process and serve as the technical bridge between Data Engineering and Analytics delivery. They will build, expand, and optimize Clarus's analytics architecture and pipelines, improving how data flows from diverse sources to downstream analytics solutions. In this role, you will lead high-impact data product and solutions initiatives from ambiguous problem definition through technical design, implementation, rollout, and adoption. You will transform raw and curated data into reliable, analytics-ready models and consistent business metrics using dbt, SQL, Python, and Databricks, while establishing a scalable architecture and strong engineering practices. The ideal candidate is a seasoned analytics engineer with strong data-wrangling skills and a passion for building and optimizing scalable analytics systems. They are self-directed, comfortable supporting multiple projects, systems, and products, and able to set technical direction while remaining deeply hands-on. What You'll Do Own analytics engineering work, including its roadmap, priorities, standards, and operating practices. Design and evolve analytics architecture, with clear responsibilities and quality expectations across bronze, silver, and gold data layers. Build, maintain, and optimize dbt models that transform source data into curated, reusable, analytics-ready datasets. Write and optimize advanced SQL, and use Python for data transformation, validation, automation, and complex processing where appropriate. Develop dimensional and business-oriented data models that support dashboards, self-service analysis, operational reporting, and data products. Establish and document shared KPI definitions, calculation logic, data contracts, ownership, and authoritative sources. Implement automated tests, source freshness checks, documentation, lineage, and monitoring to make data quality visible and dependable. Establish disciplined development practices, including Git-based version control, code review, CI/CD, and controlled promotion across environments. Partner with Data Engineering on ingestion, source schemas, platform performance, and reliable handoffs between foundational and analytical data layers. Partner with analysts, BI developers, and business stakeholders to translate requirements into scalable models rather than one-off reporting logic. Improve Databricks performance and cost efficiency through thoughtful table design, incremental processing, query optimization, and compute usage. Lead data-quality investigations, root-cause analysis, remediation, and communication when critical analytics assets do not meet expectations. Strengthen data governance by applying appropriate access controls, handling sensitive data responsibly, and supporting consistent ownership and stewardship. Migrate duplicated spreadsheet, dashboard, and ad hoc query logic into governed, tested, and reusable dbt models. Design resilient models that support historical analysis, changing source systems, incremental loads, and evolving business definitions. Create clear technical documentation, modeling conventions, and enablement materials that drive adoption of trusted data assets. Raise analytics engineering capability across the team through design reviews, reusable patterns, thoughtful feedback, and hands-on mentorship. What You Bring Bachelor's degree or higher in computer science, data engineering, analytics, information systems, mathematics, or a related discipline, or equivalent professional experience. A strong record of success leading complex analytics engineering, data engineering, business intelligence engineering, or closely related initiatives. Experience in animal health, veterinary services, pet insurance, SaaS, fintech, or health technology is a plus. 8+ years of relevant data and analytics experience, including senior-level ownership of production analytics data models and standards. Advanced SQL skills and demonstrated experience designing, debugging, and optimizing complex transformations. Deep, hands-on dbt experience, including scalable model architecture, testing, incremental models, snapshots, documentation, macros, packages, and production deployment workflows. Strong Databricks experience, including Delta Lake, Spark SQL, Workflows or Jobs, Unity Catalog, and performance management / tuning. Demonstrated skill operating medallion architectures and lakehouse data models across bronze, silver, and gold layers. Strong Python skills for data processing, testing, validation, automation, and engineering utilities. Strong understanding of dimensional modeling, warehouse and lakehouse design, semantic layers, slowly changing dimensions, and metric governance. Experience with modern engineering practices, including Git, CI/CD, code review, automated testing, orchestration, and environment management. Ability to translate ambiguous business needs into clear technical designs and communicate effectively with senior leaders and non-technical stakeholders. What Will Help You Succeed You are intellectually curious, resourceful, and motivated to understand how the business works. You take initiative, identify needs early, and you are comfortable operating in an evolving, high-growth environment. You can move easily between hands-on analytics engineering, and stakeholder conversations. You can manage production data deliverables while continuing to improve the underlying processes. You build trust by producing reliable data products, communicating clearly, and following through on commitments. LOCATION This is a remote U.S. position aligned to Eastern or Central Time business hours. U.S. travel may be required. Compensation Chicago/Boston Base pay range: $123,774 – $154,718 per year NYC Base pay range: $135,026 - $168,784 per year Miami Base pay range: $118,148 - $147,686 Nationwide Base pay range: $112,522 - 140,653 per year This is the range we reasonably expect to pay at hire. Placement within the range depends on job-related factors such as experience, skills, and certifications. This position is eligible for an annual bonus. Base pay is one part of a total rewards package that includes the benefits listed below. All of our jobs come with great benefits including healthcare, parental leave and opportunities for career advancements. Some offerings are dependent upon the location of where you work and can include the following: Comprehensive full medical, dental and vision Insurance Basic Life Insurance at no cost to the employee Company paid short-term and long-term disability 12 weeks of 100% paid Parental Leave Health Savings Account (HSA) Flexible Spending Accounts (FSA) Retirement savings plan Personal Paid Time Off Paid holidays and company-wide Wellness Day off Paid time off to volunteer at nonprofit organizations Pet friendly office environment Commuter Benefits Group Pet Insurance On the job training and skills development Employee Assistance Program (EAP) Interview Technology Notice Please note that phone and video interviews or screenings may be recorded and transcribed using interview technology to support our recruitment process. By continuing with the interview, you consent to this use. Text Messaging Notice If you provide a mobile phone number, you may receive job-related communications via text message. Message and data rates may apply. You may opt out of text communications at any time by replying "STOP."

Job Requisition ID # 26WD101381 Position Overview Autodesk's worldwide sales organization depends on its forecast, pipeline, targets and reporting. This role builds the data models behind them. As an Analytics Engineer on the Forecasting & Revenue Intelligence team, you turn sales, subscription and hierarchy data into tested, documented models that analysts and sales leaders can trust, covering what customers bought, who owns which accounts and how the sales organization looked on any given date. You will work in SQL and dbt on Snowflake, and you will work closely with the people who use your models. This is a hands-on role on a new team, and you will own what you ship. Location: United States (remote). Central or Eastern time zone preferred. Organization: Revenue Operations Responsibilities Build and maintain dbt models on Snowflake that bring Salesforce, subscription, billing, hierarchy and forecast data into a clean, documented form Model data for analysis: a clear grain, stable keys, and definitions consistent with the shared metric dictionary Keep history so any published number can be reproduced as it stood on the day it went out Maintain the mapping between accounts, territories, sellers and the sales hierarchy as the organization changes Reconcile the data to Salesforce and to Finance, and find the cause when they disagree Build the datasets behind the weekly forecast pack, business reviews and leadership dashboards Add tests and monitoring for freshness, completeness and accuracy, and fix what breaks Explain data issues and trade-offs to sales and finance partners in plain terms, and agree on a fix with them Work in version control with code review and continuous integration Minimum Qualifications Bachelor's degree in a technical or quantitative field, or equivalent practical experience 3+ years in analytics engineering, data engineering or BI development, building models other people depended on Dbt in production, with tests and documentation as part of how you work Strong SQL, including window functions and incremental models, in a cloud data warehouse such as Snowflake Working knowledge of the Salesforce data model: accounts, opportunities, line items and ownership Ability to explain a data problem to a non-technical stakeholder and reach a decision together Preferred Qualifications Dbt snapshots or slowly changing dimensions for point-in-time reporting Python for transformation or orchestration, with Airflow or similar Enterprise software or SaaS commercial data: subscriptions, renewals, territories, and direct and partner routes to market Revenue intelligence platforms such as Clari, Gong or Aviso, and BI tools such as Power BI, Tableau or Sigma Experience as an early hire on a new data team Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us! Benefits From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/ Salary transparency Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $103,000 and $185,130. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package. Equal Employment Opportunity At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law. Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging In-Person Onboarding and Identity Verification This role may require in-person onboarding and/or in-person ID verification.