Data Engineer (Bio-Technology background is a must have)

Data Engineer (Bio-Technology, Python, AWS, SQL, Terraform, Airflow, and Pandas libraries) Location: 100% Remote Duration: 6+ Months Contract You will: • Lead the architecture, design, delivery & deployment of core data platforms, data warehouse and data modeling needs. • Exceptional understanding on various data topics w.r.t. data engineering i.e. building data pipelines, data modeling , data warehousing etc. • Understanding and experience with cloud software development. Specifically AWS Cloud. • Contribute to the design and execution of data governance, data quality frameworks. • Have a passion and attention to detail for all aspects of data from ingestion, validation/quality, transformation, modeling, storage etc. • Interface with various teams from product, laboratory, web services, data science etc. Minimum Requirements: • B.S. / M.S. in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Physics, Computational Biology) with at least 6 years of related industry experience, or Ph.D. with at least 4 years of related industry experience • Substantial experience in architecting and delivering secure, scalable cloud-based data warehouses / data lakes on AWS, Azure, or Google Cloud Platform • Exceptional experience with data modeling principles , patterns and industry trends. • Very comfortable in designing and reorganizing facts and dimensions tables, complex data models, SCDs, etc. • Solid object-oriented and/or functional programming experience, specifically in Python and GO. • Expert with data pipelining and workflow engines, like Apache Airflow, Spark etc., and proven ability to choose the correct frameworks as well as tools depending on the requirements. • Experience with provisioning on AWS Cloud, e.g. with Terraform or cloudformation. Leveraging CI in a cloud environment for automation. • In depth Experience with relational databases, query authoring, and performance tuning. • Ability to take a high-level requirement and decompose that into clear engineering objectives, which can be further evolved into detailed specifications. • High emotional quotient to work with potential ambiguity, ask the right questions and engage to drive resolution from requirements to solutions. The following are highly welcome: • Proven track record of building and operating scalable data infrastructure, managing data models for hundreds to thousands of tables. • Experience with various data products, involvement in build vs buy decisions, designing a solution with limited resources and/or timelines . • Experience with DevOps, e.g. CI/CD pipelines, containerized deployment, infrastructure as code, Terraform. • Experience building microservices and web applications. • Experience with supporting data science / machine learning data pipelines. Apply Job! Apply to this Job