Data Engineer

•         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 GCP

•         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