←Back to all jobs at Freehold Royalties Senior Mineral Land Analyst Freehold is seeking a Senior Mineral Land Analyst to join our team in Calgary, reporting to the Team Lead, Mineral Land Asset Management. In this role, you will manage and administer mineral leases and contracts across Freehold's Canadian portfolio, ensuring accurate land records, compliance with contractual and regulatory requirements, and effective communication with lessors, lessees and internal stakeholders. The ideal candi…
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Class 1 Night Driver for a large client based in Bicester Start times between 17:00 - 22:00 Trunking depot to depot £22 P/h Following shift patterns available Monday to Friday Sunday to Thursday If you are interested contact Tom on 07375 648851
Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with documents through advanced PDF technology and tools. We are a leading global software provider of fast, affordable, and secure PDF solutions that are used by millions of people worldwide. Winner of numerous awards, Foxit has customers in more than 200 countries and global operations. We have a complete product line and an exciting and aggressive development schedule. Our proven PDF technology is disrupting the status quo establishment and has accelerated our company growth. We are proud to list as customers Google and Amazon, and with your skills and help, we plan to add many more. Foxit has offices all over the world, including locations in the US, Asia, Europe, and Australia. For more information, visit us @ www.foxit.com About the Role We are looking for an experienced Data Engineer to own the data pipelines that power our go-to-market systems. While this role is aligned to the marketing department's priorities, you will work day-to-day within our Business Applications & Data Analytics team, following the team's established development standards, architecture patterns, and code review processes. This ensures the pipelines you build are consistent with our broader data platform and maintainable by the wider engineering team. Your primary focus will be marketing-related data needs - working closely with demand gen, product marketing, sales operations, and digital teams to understand their requirements, then building and maintaining the pipelines and integrations that deliver on them. This is a hands-on execution role. You will build and operate the data infrastructure that connects our marketing automation platform (HubSpot), CRM (Salesforce), data warehouse (Databricks), licensing system, payment platform, and other source systems. Your work will directly support marketing's ability to segment audiences, measure attribution, and run data-driven campaigns at scale. What You'll Do Data Pipeline Development & Operations • Design, build, and maintain ETL/ELT pipelines, building upon and further optimizing our existing medallion architecture (Bronze → Silver → Gold) to move data between source systems (Salesforce CRM, HubSpot, NetSuite, Stripe, DealHub, LMS) and our Databricks data warehouse. • Build pipelines using PySpark and SQL in Databricks notebooks, following established development standards for naming, project structure, and layer-appropriate transformations. • Own the data sync layer between Databricks and HubSpot — enrichment flows inbound to HubSpot (license status, renewal dates, subscription state, firmographic data) and marketing engagement data flowing back to Databricks (email events, workflow enrollment, lifecycle changes). • Build and maintain Exchange layer pipelines that curate data for external system consumption, formatting and validating data to meet target system requirements. • Build and maintain scheduled batch jobs and event-driven integrations using APIs (REST, webhooks, OAuth). • Monitor pipeline health, set up alerting for failures and data quality degradation, and own incident response when syncs break. • Maintain documentation of data flows, integration architecture, and troubleshooting runbooks. Data Modeling & Quality • Build and maintain dimensional models in Databricks (fact tables, dimension tables, bridge tables) following our data warehouse object type definitions and naming standards. • Work in collaboration with stakeholders and data analysts to build curated, business-ready tables and datamarts that apply business logic, KPI calculations, and aggregations optimized for analytics and campaign activation. • Implement identity resolution and deduplication logic to produce unified customer profiles from multiple source systems. • Establish data validation rules, quality checks, and monitoring to ensure accuracy and freshness of data flowing into marketing systems. • Normalize disparate data sources into clean centralized schemas with proper type enforcement, deduplication, and null handling. Marketing Data & Segmentation Support • Ensure the data infrastructure supports audience segmentation, including firmographic, behavioral, and engagement signals. • Build the data layer that powers lifecycle marketing - triggered campaigns, dynamic journey branching, and personalization based on enriched customer profiles. • Support marketing and demand gen teams with reliable, accessible data for building audience targets in HubSpot. • Maintain data flows for email deliverability, subscription management, and suppression list synchronization. Integration Development • Build and maintain API integrations between marketing, sales, and operational systems using Python and SQL. • Implement field-level transformation logic, sync orchestration, and error handling for system-to-system data flows. • Support website form and lead capture data flows - ensuring clean handoff from web properties into HubSpot and Databricks. • Work with third-party enrichment providers (firmographic, intent, technographic) to integrate enrichment data into automated workflows. Reporting & Attribution • Build and maintain the data infrastructure that supports campaign attribution, channel performance analysis, and funnel reporting. • Ensure accurate data for conversion analytics, lead source tracking, and marketing ROI measurement. • Support centralized reporting by routing marketing engagement data back into Databricks for cross-functional analysis. What You Bring Required: • 5+ years of experience in data engineering, with hands-on pipeline development and production operations. • Strong proficiency in SQL and Python/PySpark for data pipeline development. • Experience building and maintaining ETL/ELT pipelines using Databricks, dbt, Airflow, Azure Data Factory, or equivalent. • Hands-on experience with cloud data platforms - Databricks, Snowflake, BigQuery, or Redshift. • Solid understanding of dimensional data modeling - fact tables, dimension tables, schema design, and data warehouse concepts. • Experience with medallion or layered data architectures (raw → cleansed → business-ready), Kimball-style star schemas, and one-big-table approaches to data modeling. • Working knowledge of API integration patterns - REST, webhooks, OAuth, batch sync architectures. • Experience with CRM platforms (Salesforce, HubSpot, or similar), marketing automation systems, and CPQ/quoting tools (DealHub or similar). • Bachelor's degree in Computer Science, Information Systems, or equivalent industry experience. Preferred: • Experience with Databricks (Delta Lake, PySpark, Unity Catalog). • Familiarity with HubSpot APIs and data model. • Experience with identity resolution and customer data deduplication across multiple source systems. • Exposure to marketing data concepts — lead scoring, audience segmentation, campaign attribution, lifecycle stages. • Experience with Azure cloud services (Azure Functions, Azure DevOps, Azure Data Factory). • Knowledge of data security and privacy practices, particularly regarding PII handling. • Experience with code review processes and development standards compliance in a collaborative data engineering team. What Sets You Apart • You've built and operated production data pipelines that marketing teams depend on daily - you understand the impact of data freshness and accuracy on campaign execution. • You're comfortable working within a marketing department and can translate data requests from non-technical stakeholders into pipeline requirements. • You take ownership of pipeline reliability - building monitoring and alerting proactively rather than waiting for someone to report a problem. • You've worked with multiple data sources and know how to handle the messiness of real-world identity resolution and deduplication. Why Join Us • High-impact work. Your pipelines will directly power how our marketing engine operates and scales. • Modern stack. Databricks, Delta Lake, PySpark, HubSpot, Python, SQL - you'll work with current tools, not legacy systems. • Room to build. We're investing in our data infrastructure as part of a major platform migration, and you'll shape how it's built. • Collaborative environment. You'll work closely with marketing, sales, and IT teams - visible, cross-functional work without being siloed. Foxit is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. 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.
Servco is hiring a Data Engineer I to build and support defined data pipelines for Hawaii Mobility. Working with internal systems and external APIs, the role helps transform, model, test, and document data so reporting, operations, and AI teams can rely on it. Reporting to the Manager, Data Engineering, within the Data Visualization, Analytics & Automation function led by its Director under the VP, Data & AI, this is an individual contributor role with coaching and code review. The engineer develops familiarity with Servco systems and takes on work with increasing independence. Key Outcomes Engineering delivery Build, test, document, and maintain defined ingestion and transformation pipelines with guidance and review. Assist with models, mappings, integration checks, lineage, and data quality for reporting and AI-ready data. Support deployment, monitoring, and troubleshooting of pipelines; escalate complex incidents and help with critical operations as needed. Partner with Analytics Engineers and senior Data Engineers to make governed data available and understandable for reporting and AI use cases, following approved solution designs. Help investigate data quality exceptions, record root causes and fixes, and keep source mappings and operating notes current under senior guidance. Assist with metadata, definitions, access requests, and lineage so downstream users can find and trust approved data. Growth and operating practice Learn Servco business systems, Databricks, Azure, Python, SQL, Git workflows, testing, and documentation through coached delivery. Follow governance and secure data handling standards while steadily expanding ownership and seeking feedback. Listen to operators and learn how customer, sales, service, and finance data supports day-to-day decisions; use feedback to improve the assigned data work. Qualifications Education: Relevant degree or equivalent experience, Databricks coursework or certification, practical SQL/Python projects, or analytics team experience. (Preferred) Work Experience Foundational SQL and Python knowledge with 1-2 years of relevant experience, projects, internships, or equivalent demonstrated skills. Skills Familiarity with data integration, basic modeling, APIs, Git, and collaborative problem solving. Exposure to Databricks, Azure, automated testing, CI/CD, and infrastructure as code is helpful; advanced proficiency is not expected at entry. Will develop knowledge of recovery, performance, scalable architecture, privacy, and cost optimization through guided work. Competencies Careful attention to quality, documentation, secure handling, and learning through review. About Servco At Servco, we're committed to providing valuable mobility solutions to empower people through the freedom of movement and opportunity. From Australia to California, and of course, Hawaii, Team Servco is a collective of over 2,000 like-minded individuals guided by our four Core Values of Respect, Service, Teamwork, and Innovation. For over 100 years, we have been dedicated to superior service, to both our customers and team members. We look forward to helping you create Life:Moments that matter to you. Interested? Visit www.servco.com/careers to apply online or email us at careers@servco.com. Equal Opportunity Employer and Drug-Free Workplace Pay Range: $72,900.00 - $110,820.00 per year
Job Title- Platform Engineer (Kubernetes) Job Type- Full-time, W2, onsite Job Location-San Francisco, CA What youll do Build and extend the Kubernetes platform core features using Go, including custom Kubernetes operators and controllers. Design and implement GitOps workflows with ArgoCD to streamline continuous deployment. Develop infrastructure-as-code patterns using Terraform and Helm to provision and manage clusters. Work on distributed storage solutions using Ceph and WEKA for high-performance, scalable storage. What we are looking for 2+ years of software development experience. Proficiency in Go and Kubernetes, with hands-on experience building developer tools or infrastructure products. Experience with distributed storage solutions such as Ceph and WEKA. For more information, please share your resume to priya@a2zxperts.com LinkedIn:
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About Typeface We help the world's biggest brands move from brief to fully personalized campaigns — in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we're building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing. What You'll Do We're looking for a Staff Infrastructure Engineer to help lead core parts of our platform. You'll design, build, and scale the cloud infrastructure that powers our AI and GenAI workloads — ensuring reliability, security, and performance as we grow. This is your chance to shape the backbone of a platform trusted by Fortune 100 companies — building systems that are resilient, observable, and ready to scale with the next wave of AI. How You'll Make an Impact: Design, deploy, and manage production-grade cloud infrastructure on AWS, GCP, or Azure to support AI/GenAI workloads at scale Build and maintain Kubernetes clusters and container orchestration pipelines for high-availability services Develop and evolve infrastructure-as-code (Terraform, Pulumi, or similar) to ensure reproducible, auditable environments Implement comprehensive observability — monitoring, logging, alerting, and tracing — to maintain system health and accelerate incident response Harden infrastructure security posture through network policies, secrets management, IAM best practices, and compliance controls Optimize cost, performance, and reliability of GPU and compute-intensive workloads that power generative AI capabilities Collaborate closely with Product, Engineering, and Security partners to define SLOs and drive continuous improvements in platform resilience Automate CI/CD pipelines and deployment workflows to enable fast, safe releases across environments Mentor and support fellow engineers, contributing to a strong infrastructure engineering culture What You Bring: 10+ years of Infrastructure, DevOps, or Site Reliability Engineering experience, with a strong track record of building and operating production systems at scale Bachelor's or Master's degree in Computer Science, Engineering, or a related field Deep expertise with Kubernetes, Docker, and container orchestration in production environments Strong proficiency with infrastructure-as-code tools such as Terraform, Pulumi, or CloudFormation Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure), including networking, compute, storage, and identity services Solid understanding of observability stacks (Prometheus, Grafana, Datadog, or similar) and incident management practices Experience with security best practices for cloud-native environments — including network segmentation, secrets management, and compliance frameworks Excellent communication skills and the ability to thrive independently and in collaborative teams Bonus: Experience scaling infrastructure for AI/ML or generative AI workloads, including GPU orchestration Location This is a hybrid role based in Palo Alto, CA. We collaborate in-office 3 days a week. Base Salary The range for this role is $210,000-$240,000 plus equity. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits Competitive compensation — including salary, equity, and 401(k) Full medical, dental, and vision insurance for you and your family HSA and FSA options to support your financial wellness Flexible time off — including parental leave Well-being programs — resources to support your mental and physical health Daily lunch & snacks Mentorship & impact — work closely with top AI leaders on products that ship Equality Opportunity Statement We welcome and encourage applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, medical condition, veteran status, or any other legally protected status. We comply with applicable laws in every jurisdiction where we operate. Why You'll Love Working Here Build something big — Be part of a fast-growing startup defining a new category: marketing orchestration powered by Agentic AI. Your work will matter — Trusted by Fortune 100 companies, our platform delivers 10x content velocity and 90% faster campaigns. A+ team — Collaborate with veterans from Meta, Amazon, Adobe, Google, Microsoft, and top AI companies. Backed by the best — GV, Salesforce Ventures, Microsoft, Lightspeed, Madrona and Menlo ($165M raised). Recognized for innovation — TIME Best Inventions, Fast Company Next Big Thing in Tech, Gartner Cool Vendor, Adweek AI Company of the Year, LinkedIn Top Startup, Webby Award (AI Work & Productivity).
Lead DevOps Engineer - GCP
Position: Lead DevOps Engineer - GCP Location: Chicago, IL Work Arrangement: Hybrid – 3 Days Onsite/Week Start Date: Immediate Availability Required Background Check: Mandatory About the Role We're looking for a Lead DevOps Engineer to spearhead the implementation of Google's Edge Platform across our enterprise infrastructure. This is a high-impact opportunity to architect and deploy resilient, scalable DevOps solutions in a mission-critical environment while guiding a growing team and influencing best practices organization-wide. Key Responsibilities: Advanced Google Cloud Platform (GCP) Architecture Design Kubernetes and Container Orchestration Build highly reusable and modular Terraform modules for multi-environment infrastructure deployments. Develop secure and automated CI/CD pipelines using tools like Cloud Build, GitHub Actions, Jenkins, or Spinnaker. Design and enforce robust Identity and Access Management (IAM) strategies using Workload Identity Federation, OIDC, and RBAC on GCP and GDCC. Integrate and manage GCP-native services such as Cloud Run, GKE, Cloud Functions, Secret Manager, and Pub/Sub. Leverage Anthos and GKE Enterprise for managing Kubernetes workloads across distributed environments. Drive infrastructure observability and logging using Cloud Monitoring, Logging, and Operations Suite. Collaborate with application, security, and DevOps teams to ensure compliance with cloud security and regulatory standards. Monitor and optimize cloud performance, cost, and scalability Required Qualifications: 7+ years in infrastructure architecture, DevOps, or cloud engineering roles. Deep, hands-on expertise with Terraform (advanced level), including reusable modules, remote state, and workspaces. Advanced knowledge of Google Cloud Platform (GCP) services and architectural patterns. Proficient in Python scripting for infrastructure automation and integration. Proven experience in building and maintaining CI/CD pipelines using Git-based workflow Deep, hands-on expertise with on Kubernetes or GKE. Preferred Qualifications: Experience with GDCC (Google Distributed Cloud) and Google Edge. Strong understanding of Cloud IAM, RBAC, and Workload Identity Federation for secure authentication across services. Solid background in cloud security, including encryption, firewall policies, VPC design, and service accounts. Why Join Us Lead a marquee initiative tied to strategic cloud transformation Work in a modern hybrid environment with smart, motivated peers Gain visibility with senior leadership and influence DevOps maturity organization-wide
Job ID 2616744 Location Washington, DC, US Date Posted 2026-09-11 Category Software Subcategory SW Engineer Schedule Full-Time Shift Day Job Travel No Minimum Clearance Required None Clearance Level Must Be Able to Obtain Public Trust Potential for Remote Work ORA_ON_SITE Description Job Summary We are seeking a mid-level Google Cloud Platform (GCP) Engineer with strong, hands-on experience across cloud administration, automation, system integration, and application support. This role supports production GCP environments and participates in cloud migration initiatives, including on-premises to cloud and cloud-to-cloud migrations. This position prioritizes real-world, operational experience over certifications. While Google Cloud certifications are valued, demonstrated hands-on experience designing, deploying, automating, migrating, and supporting GCP workloads in production environments carries significantly more weight. Experience with data engineering and analytics platforms is a strong plus but not a strict requirement for candidates with a proven track record of strong GCP engineering experience. Must be able to work onsite on a full-time basis! Remote positions will be considered depending on skills, qualifications, and availability during 7AM-7PM Eastern support window. Qualifications Job Role Specific Requirements Bachelor's Degree and 5+ years of experience or Master's Degree and 3+ years of experience. GCP Administration & Operations Administer and support GCP organizations, folders, projects, and billing Manage IAM roles, service accounts, and access controls using least-privilege principles Configure and maintain VPC networks, firewall rules, VPNs, and hybrid connectivity Monitor platform health using Cloud Monitoring, Logging, and Alerting Troubleshoot production issues and perform root-cause analysis Support environments across development, test, staging, and production Automation & Infrastructure as Code Design, deploy, and maintain infrastructure using Infrastructure as Code (IaC) Terraform (preferred) Deployment Manager (where applicable) Automate operational and lifecycle tasks using Cloud Functions, Cloud Run, Workflows and Cloud Scheduler Develop and maintain scripts using Python and/or shell scripting Reduce manual effort through standardization and automation Cloud Migration & Modernization Support cloud migration initiatives, including On premises to Google Cloud migrations Cloud-to-cloud migrations (e.g., AWS or Azure to GCP) Assist with Migration planning and execution Workload and dependency analysis Data, application, and infrastructure migrations Support cutovers, post-migration stabilization, and optimization Help modernize legacy workloads into cloud-native or hybrid architectures Integration & Platform Engineering Integrate GCP services with enterprise systems such as Identity platforms (Google Workspace, Active Directory, SSO) CI/CD pipelines and automation tooling SaaS and internal applications Support API-based and event-driven integrations using REST and Pub/Sub Collaborate with security, networking, and application teams Assist with hybrid and multi-cloud integration patterns Application & Development Support Support applications deployed on Compute Engine, GKE, Cloud Run and App Engine Assist development teams with Environment provisioning Deployment pipelines Performance and reliability tuning Review cloud architectures for scalability, resilience, security, and cost Data & Analytics (Strong Plus) Support data platforms such as BigQuery, Cloud Storage, Pub/Sub, Dataflow Assist with data ingestion pipelines and analytics workloads Understand basic data governance, access controls, and performance tuning Required Skills And Qualifications Active public trust and/or DOT on-boarded is a strong plus 3–6 years of hands-on experience working with Google Cloud Platform in production environments Proven experience administering and supporting GCP services Note Candidate must be a U.S. citizen or green card holder who has resided in the U.S. for at least 3 years and the ability to obtain public trust. Target salary range $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
Title : GCP Cloud Engineer/Architect Location : Remote Clearance: Must be a US Citizen eligible to OBTAIN a Secret Clearance Position Overview The GCP Cloud Engineer supports federal cloud modernization initiatives by designing, implementing, and optimizing secure, scalable Google Cloud Platform (GCP) environments. This role focuses on professional services delivery, cloud architecture, and hands-on engineering rather than operations and maintenance. The engineer collaborates with application, data, cybersecurity, and DevSecOps teams to enable modern, resilient cloud solutions. Required Qualifications 4–6+ years of hands-on cloud engineering experience Strong experience with Google Cloud Platform (GCP) Kubernetes/GKE deployment and operations experience Cloud networking expertise (VPC, subnets, routing, firewall rules, load balancing) Experience with IAM, service accounts, and organization policies Proficiency with Terraform and Infrastructure-as-Code practices Familiarity with Linux, containers, YAML, and CI/CD pipelines Strong communication and customer-facing skills Ability to work independently and manage ambiguity Preferred Qualifications GCP Professional Architect or Security Engineer certification Experience with BigQuery, Dataflow, Firestore, or Vertex AI Experience with Crossplane, Ansible, or similar automation frameworks Exposure to Splunk, Cribl, Databricks, or similar analytics platforms Knowledge of FedRAMP, NIST 800-53, or federal cloud environments Java application deployment or modernization experience Veteran status strongly encouraged Core Responsibilities Design, implement, and maintain GCP infrastructure supporting modernization initiatives Architect and deploy Kubernetes (GKE) clusters and supporting services Lead migrations from on-premises environments to cloud-native architectures Design and implement cloud networking solutions including VPCs, routing, firewalls, and VPN/interconnects Develop Infrastructure-as-Code using Terraform and Kubernetes-native tooling Implement CI/CD and GitOps workflows using GitHub or GitLab with ArgoCD/Argo Workflows Support data and application platforms including BigQuery, Dataflow, Cloud Run, Firestore, and Pub/Sub Provide architecture guidance, documentation, and best-practice recommendations Collaborate with security teams to ensure compliance with federal and enterprise standards Position Characteristics Professional services and modernization focused Customer-facing engineering role Opportunity to grow into a multi-cloud or multi-OEM subject matter expert Powered by JazzHR VSB1198gO3
Job Title: ON-SITE - Google Cloud Platform Platform Engineer - HBITS-08-15062 Location: New York City, NY 10004 Duration: Long term (30) Job Description 60 months of experience in cloud infrastructure, DevOps, or systems administration, including at least 2 years in a public cloud environment (Google Cloud Platform preferred; AWS or Azure considered) 36 months of experience with Google Cloud Platform, including Compute Engine, Cloud Storage, VPC networking, IAM, and Secret Manager 36 months of experience with Terraform, including reading, writing, and modifying infrastructure code within established patterns 36 months of experience building and maintaining CI/CD pipelines using Cloud Build, GitHub Actions, or equivalent 36 months of experience with GitHub and Git workflows, including pull requests and branch management 24 months of experience in an Agile delivery environment, including sprint ceremonies and iterative delivery 12 months of experience with DataDog for log analysis and observability 12 months of experience with static code analysis tools such as SonarQube within a CI/CD pipeline Bachelor's Degree Google Cloud Associate Cloud Engineer or Terraform Associate (HashiCorp) Agency: Department of Financial Services Detailed Job Description: The Platform Engineer (Mid-Level) is a hands-on engineering role on the newly established DFS Platform Services team. This role contributes directly to building, operating, and maintaining the internal platform that enables development and operations teams to ship software faster and more reliably. The candidate will work under the guidance of the Lead and Senior Platform Engineers in a structured, mentorship-rich environment. Note: Sorry we do not Sponsor Visa Max: SEVEN 32.800.2838 Aryan: - SEVEN 32.444.8990
Job Description Job Description We are seeking a highly skilled Cloud Engineer Subject Matter Expert (SME) to join our team. The Senior Cloud Engineer (Cloud Engineer SME) is the senior technical implementation lead responsible for designing, building, and operationalizing secure, scalable AWS-based environments supporting modernization of complex, interdependent systems. This role requires deep AWS engineering expertise and advanced Python development skills, as well as active participation in discovery, legacy system analysis, and phased migration planning. The Cloud Engineer SME will work closely with the Systems Architect and Technical Program Manager to assess existing environments, design migration-ready architectures, and implement cloud-native solutions aligned to modernization sequencing and governance requirements. This is not a pure infrastructure role — the Cloud Engineer SME must be capable of analyzing legacy systems, evaluating migration paths, and translating architectural strategy into deployable cloud solutions. Key Responsibilities Write production-quality Python code with testability, logging, secure coding practices, and modular design. Review and support Python refactoring patterns during legacy modernization. Ensure Python runtime environments are reproducible and aligned with CI/CD standards. Embed quality and compliance gates into pipelines. Automate environment provisioning and deployments. Ensure version-controlled infrastructure and reproducible deployments. Discovery, Legacy Analysis & Migration Planning Participate in structured discovery efforts across legacy systems. Analyze existing application architectures, infrastructure dependencies, batch schedules, data flows, and integration points. Contribute to formal system inventory documentation. Identify cloud readiness gaps and modernization constraints. Support classification of systems using the 7 Rs migration framework. Provide technical input into phased migration roadmaps and sequencing plans. Assess operational risk, integration complexity, and environment dependencies during modernization planning. Document current-state (As-Is) technical architecture and assist in defining target-state (To-Be) environment patterns. Cloud Infrastructure & Environment Engineering Design and implement AWS cloud environments aligned to enterprise provisioning constraints. Develop and maintain Infrastructure-as-Code (IaC) using Terraform or CloudFormation. Establish repeatable environment patterns for development, testing, staging, and production. Implement secure network architecture (VPC segmentation, IAM least privilege, encryption). Design for high availability, resiliency, and disaster recovery. Align environment provisioning with migration waves and modernization sequencing. Python Engineering for Cloud-Native Applications (Required) Develop and maintain Python-based cloud components including: Serverless functions Orchestration utilities Data validation and transformation scripts Automation tooling Cloud-Native Application Enablement Implement scalable AWS compute solutions (Lambda, ECS/EKS/Fargate, Glue, Aurora/PostgreSQL, S3, Batch). Evaluate serverless vs containerized approaches based on workload characteristics. Support refactoring efforts by providing optimized cloud runtime patterns. Improve performance, scalability, and observability for data-intensive workloads. DevSecOps & CI/CD Implementation Design and implement CI/CD pipelines integrating: Automated builds Unit and integration tests Regression validation Security scanning Observability & Operational Readiness Implement monitoring, logging, and alerting standards. Establish performance baselines and capacity thresholds. Support load testing and scalability validation. Document operational runbooks for sustained support. Cross-Team Integration Support Support integration across multiple interdependent systems. Assist in identifying and mitigating interface risks. Collaborate with data engineering teams on schema stability and data lifecycle controls. Ensure consistency in cloud patterns across teams. Governance & Compliance Alignment Contribute to architecture and environment documentation required for governance reviews. Support ATO readiness and audit artifact collection. Align cloud implementation with security and compliance requirements. Maintain traceable, auditable deployment documentation. Core Competencies Ability to translate discovery findings into technical modernization solutions. Strong cloud engineering depth combined with legacy system analysis capability. Migration sequencing awareness and risk identification. Automation-first engineering mindset. Strong documentation and communication skills. Ability to operate effectively within structured modernization programs Requirements Bachelor's degree in Computer Science, Engineering, or related field. 8+ years of professional experience in cloud engineering. Advanced Python expertise for cloud-native applications and automation. Demonstrated experience performing legacy system analysis and cloud readiness assessments. Experience contributing to migration plans using structured frameworks (including 7 Rs). Strong AWS expertise across compute, networking, storage, database, identity, and monitoring services. Experience implementing Infrastructure-as-Code. Experience implementing CI/CD pipelines and automated testing. Strong troubleshooting, performance optimization, and systems integration skills. Preferred Qualifications Experience supporting data-intensive or statistical processing systems. Experience supporting SAS-to-Python modernization efforts. AWS Certified Solutions Architect certification. Experience in regulated or governance-heavy environments. Experience working within enterprise data lake ecosystems. Benefits 401(k) 401(k) matching Dental insurance Flexible spending account Health insurance Life insurance Paid time off Professional development assistance Referral program Tuition reimbursement Vision insurance
AWS Cloud Engineer – Remote 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: AWS Cloud Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$110,000 Annually Experience Required: 6+ 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 We are seeking an experienced AWS Cloud Engineer to design, build, and operate large-scale, secure, and highly available cloud platforms on Amazon Web Services. This is a deeply hands-on engineering role spanning architecture, infrastructure-as-code, automation, security, observability, and continuous operational improvement of mission-critical production workloads. The successful candidate will bring strong working knowledge of the AWS service portfolio, deep DevOps fundamentals, and a pragmatic, cost-aware design mindset, and will partner with application, security, and SRE teams to deliver resilient, cloud-native solutions that scale with the business. Required Qualifications Bachelor's degree in Computer Science, Engineering, or a related technical discipline Five or more years of cloud engineering experience, with at least three years focused on AWS in production environments Strong hands-on experience with AWS core services, including EC2, VPC, IAM, S3, RDS, Lambda, CloudFront, and CloudFormation Production-grade experience with infrastructure-as-code tools such as Terraform, AWS CDK, or CloudFormation Solid experience designing and operating Amazon EKS or ECS clusters at scale Hands-on experience with CI/CD pipelines across infrastructure and application workloads Strong scripting skills in Python and Bash, with familiarity in Go or PowerShell considered a plus Deep understanding of cloud security, IAM, encryption, key management, and compliance requirements Experience implementing observability, monitoring, and alerting in cloud-native environments Strong troubleshooting, communication, and documentation skills Preferred Qualifications AWS Certified Solutions Architect – Professional or DevOps Engineer – Professional certification Experience with multi-account AWS Organizations and centralized governance Familiarity with service mesh, eBPF-based observability, and zero-trust networking Exposure to FinOps practices and well-architected cost-optimization frameworks Experience operating regulated workloads (HIPAA, PCI-DSS, SOC 2, FedRAMP) How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to hilda@bvteck.com 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. Powered by JazzHR lhvVrEgOFq