Data Engineer

Function Health is hiring a Data Engineer to build platform engineering that enables safe, fast data, analytics, and machine learning changes for engineers and agents.

Responsibilities

• Build and maintain the event pipeline behind product analytics, experimentation, and feature gates.
• Enforce schemas at the source so invalid events never become invalid metrics.
• Operate a Databricks lakehouse with Bronze, Silver, and Gold layers.
• Implement automated schema evolution and contract tests.
• Create backfills that are safe and not disruptive.
• Generate freshness and volume monitors from the contract rather than adding monitors later.
• Build pipelines for feature computation and feature serving, plus training and evaluation workflows.
• Integrate the plumbing that returns model outputs back into the product using the same standards for testing and observability.
• Improve self-service through templates and local dev and preview environments.
• Apply policy-as-code for PHI and implement ownership routing for alerts.
• Enable progressive gates so exploratory models ship with less friction while member-facing models receive more scrutiny.

Requirements

• Experience building internal platforms or infrastructure that other engineers actually adopt.
• Experience operating production data or ML systems, including on-call coverage and incident response under pressure.
• Strong Python and SQL.
• Comfort working in a lakehouse (Databricks experience is part of the role; Snowflake or BigQuery experience translates).
• Ability to design interfaces and schemas other teams depend on, and evolve them without breaking downstream needs.
• Thoughtful approach to testing and CI for data or ML, especially where correctness is statistical and failures may be silent.
• 1 to 4 years of engineering experience (focus is on what you built, not just years).

Technologies

• Python, SQL
• Databricks, Snowflake, BigQuery
• dbt, DLT, Dagster, Airflow
• Kafka
• Spark Structured Streaming
• Terraform

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 experience
• PHI or HIPAA experience

Core values

• Ruthless Prioritization
• Member-First, Always
• One Team, Moving Fast
• Radical Ownership, Relentless Execution
• Mission Over Ego
• Sustained Integrity in Every Detail

Location

• Remote (remote)

Minimum experience: 1 years