Recursion - Sr. Data Platform Engineer - Computer System Validator

• Build, scale, and operate in a validated data platform. You will be a member of the platform team responsible for building, operating, and tuning a data platform with petabyte scale data, and maintaining a GxP-compliant data platform for clinical data. These platforms allow our users to discover and query across the breadth of our data at Recursion, which includes a chemistry library of billions of compounds, cellular microscopy images taken in millions of different experimental contexts, and millions of assay results, all supporting Recursion’s drug discovery. • Build, scale, and operate in a validated data platform • Engineer Data Integrity and Traceability: You will ensure data flows with integrity in the validated environment by building the automated audit trails and lineage required by 21 CFR Part 11 making our datasets in the clinical datalake queryable and relatable for regulatory questions. Additionally, you'll work with biologists, chemists, and data scientists to build relatability and query-ability into these datasets so they can be used in the future to answer the sorts of questions we haven't even thought of asking yet. • Act as a mentor, coach, and sponsor. You will share your technical knowledge and experiences, delivering impact, learning, and growth across teams at Recursion. • Act as a mentor, coach, and sponsor. • The Team You’ll Join • You will join the Data Lake team that built and maintains our Data Lake/house. The team is responsible for relational and object storage and has the motto: all data flows to the Data Lake. The team solves the problem of making our diverse data discoverable, queryable, and relatable across datasets while we continue to add new data modalities as we grow. This will require collaboration with many different groups including teams building out reports, dashboards, and applications, teams finding and generating the required data for machine learning problems, and teams building and iterating on new data processing pipelines. • all data flows to the Data Lake • Nice to Haves: Experience in a regulated environment (Fintech, Medicine, Nuclear Industry, etc.), Experience with Search (Elasticsearch), Vector/Graph databases, or deep experience scaling within the GCP ecosystem is a significant plus.