Staff Software Engineer, Data Platform

Function Health•US - Remote,

About The Position

Function Health is hiring a Staff Software Engineer, Data Platform, to build platform infrastructure that enables engineers and subject-matter experts to safely change and ship data and machine-learning systems. The role focuses on making the safe path the fast path through declarative contracts, data-aware CI, validation gates, lineage, and one-command rollback. The engineer will work across three areas: event tracking infrastructure for product analytics, experimentation, and feature gates; Databricks data-processing infrastructure spanning Bronze, Silver, and Gold layers; and ML infrastructure for feature computation and serving, training and evaluation pipelines, and returning model outputs to the product. The role also develops self-service capabilities such as templates, local development and preview environments, PHI policy-as-code, alert ownership routing, and progressive gates based on risk. Function Health describes its mission as helping people live 100 healthy years through comprehensive health testing, imaging, longitudinal data, and guidance from AI and clinical teams. It is building an integrated health platform and values action, collaboration, member focus, ownership, and accuracy.

Requirements

Experience building internal platforms or infrastructure adopted by other engineers.
Experience operating production data or ML systems, including on-call responsibility and resolving issues under pressure.
Strong Python and SQL skills.
Comfort working in a lakehouse; the company uses Databricks, and Snowflake or BigQuery experience is transferable.
Experience designing interfaces and schemas used by other teams and evolving them without breaking downstream users.
Experience thinking deeply about testing and CI for data or ML systems, where correctness may be statistical and failures may be silent.
8 or more years of engineering experience; the posting emphasizes demonstrated work over years of experience.

Nice To Haves

Experience with declarative pipeline frameworks such as dbt, DLT, Dagster, or Airflow.
Streaming experience with Kafka or Spark Structured Streaming.
Experience with data contracts, data diffing, or lineage tooling.
Terraform experience.
Feature store experience.
MLOps and evaluation tooling experience.
Experience with agentic coding workflows.
Healthcare experience.
Experience with PHI or HIPAA.

Responsibilities

Build and improve event-tracking infrastructure for product analytics, experimentation, and feature gates, including source-enforced schemas.
Develop data-processing infrastructure in Databricks across Bronze, Silver, and Gold layers, including automated schema evolution, contract tests, backfills, and contract-generated freshness and volume monitoring.
Build ML infrastructure for feature computation and serving, training and evaluation pipelines, and integrating model outputs into the product.
Create self-service platform capabilities, including templates and local development and preview environments.
Implement policy-as-code for PHI, ownership routing for alerts, and progressive gates that apply scrutiny according to the risk of a model or change.
Build guardrails such as declarative data contracts, data-aware CI, promotion validations, lineage, and rollback mechanisms.
Operate production data or ML systems, participate in on-call support, and resolve incidents under pressure.
Design and evolve interfaces and schemas that other teams depend on without breaking those teams.