Gilead Sciences is looking for a Sr. IT Data Engineering Manager to join the General and Administration (G&A) Data & Analytics team. This is a critical role responsible for executing on high value data ingestion, providing technical review across all Gilead Sciences G&A Systems connectivity, and piloting new approaches to modernize our tech stack. The ideal candidate will have opinions on how Data Engineering should be implemented while being open minded to feedback from peers. There will be a strong component of “leading by example” as the team standardizes the way solutions are developed in general. This role will interface with cross-functional teams at Gilead Sciences, and key stakeholders. Communication of technical content to an audience of varied technical experience is important.

• Design, Develop and Optimize AWS services with AWS Cost Explorer, Performance Insights, and Well-Architected Tools.

• Deliver data ingestion identified by Product owners.

• Design data ingestions, including source data characteristics, destination data store requirements, and performance and scalability needs.

• Participate in and lead code reviews focused on ensuring the code’s correctness, efficiency, robustness, and readability.

• Propose and advocate for development standards (patterns, processes, tools, etc.)

• Manage implantation partner’s resources and provide work instructions.

Basic Qualifications

• BS in a technical discipline and 8+ years of building enterprise data platforms

OR

• HS diploma and 10+ years of building enterprise data platforms

• Experience building data solutions using AWS services such as Appflow, Airflow, Redshift etc

• Proficiency in Python 3.6+ OR proficiency with a similar language and familiarity with Python 3.6+

• Proficiency in SQL

• Experience deploying applications using Terraform or a similar tool

• Experience building CI/CD pipelines using GitHub Actions or a similar tool

• Proficiency in managing code as part of a team using GitHub

• Familiarity with agile development methodologies

• Experience building data-driven unit test suites for data platforms

• Experience modelling highly dimensional data

Preferred Qualifications

• Experience in the biotech industry, or another highly regulated industry

• Knowledge of SRE practices

• Knowledge of Observability practices

• Experience building developer documentation with tools like sphinx and GitHub Pages

• Experience with Databricks, Starburst, ThoughtSpot, Tableau, or SpotFire

• Experience with Domain Driven Design for data modelling