Data Engineer

Nava Benefits

9d • Remote

About The Position

Nava is seeking a Data Engineer to manage the external data pipelines that feed into Nava’s domain models. This role involves ingesting health and benefits data from various sources in multiple formats, normalizing it to Nava's canonical models, and mapping and validating it for integration within the Nava ecosystem. The data team is focused on ensuring the quality, hygiene, and usability of external data. This position is crucial as clean, connected data enables Nava's AI features, enhances the member experience, and supports data-driven client conversations. The Data Engineer will be responsible for end-to-end pipeline ownership, unifying the census platform, scaling data processing, making data mapping explainable, building supporting tooling, and ensuring the production-level operation of these systems, including secure handling of sensitive data.

Requirements

• Hands-on ownership of a production data pipeline that other teams depended on (building, inheriting, or owning a stage like ingestion, normalization, mapping, or validation).
• Proficiency in Python and SQL, including joins, indexes, query plans, and performance optimization.
• Experience with a production orchestrator (Dagster preferred; Airflow or Prefect are comparable) and a cloud-based relational database like Postgres.
• Experience with proof habits: reconciliation, data-quality gates, and robust testing.
• Experience with AI-assisted development as a daily workflow.
• Care with sensitive data and clear communication with non-technical stakeholders.

Nice To Haves

• Hands-on dbt experience is a strong plus.

Responsibilities

• Own ingestion end to end: Ensure external data sources land through pipelines that fail loudly on bad input, reconcile counts from source to normalized tables, and surface problems proactively.
• Unify the census platform: Consolidate employee eligibility and elections data processes under a unified set of mapping, validation, and testing practices.
• Scale data processing: Improve pipeline efficiency to handle a significant increase in data volume without a proportional rise in cost or run time.
• Make mapping and identity explainable: Ensure member IDs, eligibility, and claims are accurately associated with the correct individuals through logged and reviewable decisions.
• Build tooling around data pipes: Develop observability and automation tools, including TypeScript web applications and AI assistance for tasks like name matching.
• Run as production software: Implement alerts for failures and data-quality regressions, ensure idempotent re-runs, manage routine backfills, and securely handle sensitive data like SSNs and health information.

Benefits

• Real ownership on a concentrated data team.
• Work that visibly unlocks Nava’s AI features, member experience, and broker conversations.
• A direct line to the engineers and leaders making product and platform decisions.
• A remote-first company with a mission to fix healthcare.
• Tooling to do the best work of your career.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed