Data Engineer

Role overview

A Data Engineer role owning the external data pipes that feed healthcare benefits data into canonical domain models. The work focuses on ingesting messy sources such as eligibility files, carrier feeds, member IDs, enrollment elections, and claims, then normalizing, mapping, and validating them so they connect cleanly to everything else known about an employer and their people. The role sits on a concentrated data team where pipeline decisions set the practice as data volume grows roughly 40× in the coming year.

Responsibilities

- Own ingestion end to end, with pipelines that fail loudly on bad input, reconcile counts from source to normalized tables, and surface problems before downstream teams or clients notice - Unify employee eligibility and elections data under a single set of mapping, validation, and testing practices with reconciliation proving each change before it ships - Revisit storage and orchestration decisions (OLAP vs OLTP, event streaming vs nightly jobs) so the platform absorbs ~40× growth without proportional cost or runtime increases - Make member ID, eligibility, and claims associations logged and reviewable so incorrect associations are caught internally and never reach a member - Build observability and automation tooling, including TypeScript web applications and AI-assisted matching where exact rules fall short - Run as production software with alerts, idempotent re-runs, routine backfills, and careful handling of SSNs and health information

Requirements

- Hands-on ownership of a production data pipeline other teams depended on, including messy external sources and downstream users who noticed when data was wrong - Python and SQL depth, exercised without leaning on AI assistance for fundamentals - Experience with mapping, normalization, validation, data-quality gates, and tests you would trust at 3 a.m. - AI-assisted development as a daily workflow, with sound judgment about what to delegate - Care with sensitive data and clear communication with people who do not write code

Nice to have

- Hands-on dbt experience - Familiarity with Dagster, dbt, Python on Postgres and AWS, TypeScript tooling, and adjacent systems like Airbyte, Parabola, and Salesforce - Small, senior data team with direct access to engineering and product leadership - Remote-first culture with a mission tied to fixing healthcare