Data Engineer
Summary
Data engineer at Function Health building internal data platform infrastructure: the product analytics event pipeline, the Databricks Bronze/Silver/Gold lakehouse, and ML feature/training/serving infrastructure — with contracts, CI, and observability so engineers and agents can safely make changes themselves. Core tech: Python, SQL, Databricks.
Company Overview
Role
Key Responsibilities
- Tracking infrastructure. The event pipeline behind product analytics, experimentation, and feature gates. Schemas that are enforced at the source, so a bad event never becomes a bad metric.
- Data processing infrastructure. The Bronze → Silver → Gold layer in Databricks. Automated schema evolution, contract tests, backfills that aren't scary, freshness and volume monitors generated from the contract rather than bolted on after.
- ML infrastructure. Feature computation and serving, training and eval pipelines, and the plumbing that gets model output back into the product — with the same testing and observability bar as everything else.
- Cutting across all three. The self-service story. Templates, local dev and preview environments, policy-as-code for PHI, ownership routing for alerts, and progressive gates so an exploratory model ships freely while a member-facing one earns more scrutiny.
Qualifications/Skills
- Built internal platform or infrastructure that other engineers actually adopted. You've felt the difference between shipping a tool and getting it used.
- Operated production data or ML systems, on call for them, and fixed them under pressure.
- Strong Python and SQL. Comfortable in a lakehouse – we use Databricks; Snowflake or BigQuery translates fine.
- Designed interfaces and schemas that other teams depend on, then evolved them without breaking those teams.
- Thought hard about testing and CI for data or ML, where correctness is statistical and the failure is often silent.
- 1-4 years of engineering experience gets you here, but we care about what you've built, not the number.
Nice-to-Have Skills and Experiences
- Declarative pipeline frameworks (dbt, DLT, Dagster, Airflow)
- Streaming (Kafka, Spark Structured Streaming)
- Data contracts, data diffing, or lineage tooling
- Terraform
- Feature stores
- MLOps and eval tooling
- Agentic coding workflows
- Healthcare
- PHI, or HIPAA experience
To be a strong fit, you embody our Core Values
- Ruthless Prioritization:
- We don’t let perfect get in the way of progress.
- We move quickly to drive value, not perfection.
- We prioritize what drives impact.
- We never compromise on standards of excellence.
- Member-First, Always:
- We design and deliver like we’re caring for someone we love.
- We create calendar, actionable, human experience.
- We prioritize responsiveness, peace of mind, and outcomes.
- We empower members with truth, clarity, and care.
- One Team, Moving Fast:
- We are aligned in purpose, prioritization, and speed.
- We gather diverse perspectives to make informed decisions.
- We clear paths for each other and move fast together.
- We communicate clearly and respectfully, rallying around shared goals.
- Radical Ownership, Relentless Execution:
- We don’t just ship– we own outcomes and drive results.
- We act with urgency and precision
- We anticipate, initiate, and follow through.
- We meet challenges with grit and pragmatism.
- We embrace new tech to deliver better outcomes.
- Mission Over Ego:
- We are ruthlessly aligned to our mission - and leave ego at the door.
- We disagree and commit.
- We don't tolerate politics or withholding information.
- We operate with honesty, transparency, and respect.
- Sustained Integrity in Every Detail:
- We earn trust by obsessing over accuracy, quality, and clarity in everything we do.
- We prioritize clinical precision - data must be right.
- We sweat the details because outcomes depend on them.
