Data Engineer
Description
NO C2C and NO SPONSORSHIP AVAILABLE
This is for candidates that are local to the St. Louis MO area only
Is Data your thing? Crunching and cleansing data get you going? Well, we have a great new position for you below
Data Engineer (Mid-Level)
Primary responsibilities
Lead and participate in design sessions with Engineering teams, Data Scientists, Product Managers, business, and Information Technology (IT) stakeholders, that result in documentation for data processing, storage and delivery solutions
Understand business capability needs and processes as they relate to IT solutions through partnering with Product Managers and business and functional IT stakeholders, and apply this knowledge to defining business problems that need to be solved
Initiate and lead evaluation of new technologies including performing POCs and presenting results to others, with a goal of providing technical recommendations
Help the team establish and improve processes and methodologies, like SCRUM or Kanban, and/or lead piloting new ones
Implement data solutions according to design documentation using a variety of tools and programming languages, like AWS and GCP cloud solutions, Kafka, SQL and non-SQL databases, Python, Scala, Go etc., and follow teams established processes and methodologies
Facilitate and participate in code reviews, retrospectives, functional and integration testing and other team activities focused on improving quality of delivery
Provide reliable estimates for large scale projects
Initiate collaboration with Product Owners, other engineers and data stewards within the team and across data, technical platforms and product teams on planning and aligning roadmaps, delivery dates and integration efforts
Required Qualifications:
Educational preparation or applied experience in at least one of the following areas, Engineering, Operation Research, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science or other related quantitative discipline
Strong level of experience building data models using R, Python or other statistical and/or mathematical programming packages Strong experience with engineering data intensive software using streaming and resource-based design principles
Technical expertise and advocate of software development best practices (Version Control, Code Documentation and Review, Cloud Based Sequence Analysis, Database Management)
Experience with at least one cloud native data warehouse database, BigQuery, Redshift, Snowflake etc.
Experience with DevOps methodologies including Infrastructure as Code concept
Experience with Cloud native technologies for processing data at scale and delivering data pipelines including Kafka, Spark, AWS SQS, Lambda, Step functions, ECS, Fargate, Athena, BigQuery, GCP PubSub, Cloud functions, Cloud Run, Kubernetes
Demonstrated advanced business acumen, people and project leadership competencies, and technical expertise
Excellent communication skills with the ability to communicate complex qualitative analysis in a clear, precise and actionable manner and deliver presentations to large audiences, executive leadership, and externally at conference and collaborations
Apply immediately to beat the rush!!
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