Senior Data Engineer

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.

We are building the Patient Evaluation Engine: a high-scale, multi-modal healthcare platform where autonomous AI agents reason over clinical data to drive real-time clinical evaluation across federated networks of hospitals.

Build the pipelines that feed the agents. Develop the systems that fetch, parse, and serve both structured and unstructured data in formats optimized for real-time inference — spanning clinical EHR records, high-throughput genomics (NGS), and cardiovascular imaging (Echo, Cath, ECG). Own the warehouse and its transformations. Build and maintain our dbt models on Big Query, along with the tests, documentation, and SQL standards that keep a growing model layer trustworthy.

Model the multi-modal patient record. Shape the data model across those domains, applying normalized and dimensional design as each one demands, and write the code that enforces it. Move data through event-driven services. Build and operate the Pub/Sub topics, subscriptions, and dead-letter handling that connect ingestion, evaluation, and result delivery, with the retry and idempotency behavior that reliability at scale requires.

Make the data agent-ready. Build the data access patterns and metadata layers that let AI agents autonomously discover, query, and reason over structured and unstructured datasets, and the retrieval services those agents call. Write the software on top. Build the Type Script services and APIs that handle agent input and output and coordinate specialized agents, meeting the platform's performance and scalability demands.

You are expected to be comfortable in the application codebase, not only in the data layer. Own the infrastructure your platform runs on. Extend and operate the platform's Google Cloud footprint in Terraform — Big Query datasets, Pub/Sub, Cloud SQL, Cloud Storage, Memory store, Secret Manager, and the service-account and IAM model that governs access to clinical data. Scale across hospital networks.

Build for federated networks of hospitals: multi-tenancy, high availability, and performance across hybrid on-prem and cloud environments built for sensitive health-system integrations. Guarantee ground truth. Implement automated solutions to monitor data quality and lineage with strict traceability back to source systems, ensuring "ground truth" for agentic evaluations. Instrument for trust. Build the observability, error tracking, and human-in-the-loop checkpoints that make automated clinical evaluation transparent and debuggable.

Raise the standard around you. Partner with clinical, analytics, and platform engineering teams on data modeling standards, governance, and practices for maintaining data integrity in a HIPAA-regulated environment.

We care about these as much as the technical checklist. High ownership. You own what you build all the way into production — you care whether it stays up, you chase root causes instead of symptoms, and you do not treat the deploy boundary as the end of your responsibility. Self-starter. The problem space is genuinely open. You are comfortable identifying the most valuable next thing and starting on it without a fully specified ticket, and you surface ambiguity early rather than stalling on it.

Collaborative. You work directly with clinical, analytics, and platform engineering partners. You write things down, you explain trade-offs to non-specialists, and you make the people around you faster. Quick to add impact and value. You bias toward shipping something real and incremental early over long design cycles, and you look for the change that moves the platform now.

Warehouse and transformation:
Big Query, dbt. Operational data stores:
Cloud SQL (PostgreSQL),…