Senior Manager, Software Engineering (Data Architecture)

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

About Tempus

Tempus is on a mission to create the world’s largest integrated dataset of clinical and molecular data. We believe that, through data, we can make a lasting contribution to cancer research and treatment. At Tempus, products are owned and developed by small, autonomous teams of developers, designers, data scientists, and product managers who work together to build a platform that is both nimble and innovative.

The Role

As Senior Manager, Software Engineering, you will lead and mentor a small team of data engineers and data architects, and you will own the enterprise data model and the reliability of the data it represents. You will design how clinical records, genomics, next-generation sequencing (NGS) laboratory data, and radiology data are integrated, and you will ensure that the data are accurate, traceable, and suitable for critical applications such as machine learning and clinical decision-making.

You will establish modeling standards, implement quality gates in data pipelines, and develop the team through design review, code review, and ongoing coaching. You will use development tools assisted by artificial intelligence (AI) to accelerate design, testing, and delivery.

What You Will Do

• Lead and mentor a small team of data engineers and data architects by conducting design and code reviews, providing technical guidance, and fostering a culture of excellence in data architecture and data quality.
• Own and evolve an enterprise data model with engineers, product managers, scientists, and operators, integrating structured data from clinical records, genomics, the NGS laboratory, and radiology across relational and NoSQL data stores. Author and maintain entity-relationship diagrams, data dictionaries, API specifications, and data-translation documentation at the conceptual, logical, and physical levels.
• Apply modern data architecture best practices and patterns, and teach modeling standards, including third normal form, dimensional (star schema) design, and established healthcare data model standards such as FHIR, OMOP, and related standards.
• Evaluate the completeness of source-system models and partner data through profiling, and resolve structural inconsistencies before they reach downstream consumers.
• Design observability for the data ecosystem with BigQuery, dbt, Elementary, and Grafana, including monitors, alerts, dashboards, lineage, and traceability back to source systems.