Data Engineer

🕒 September 15

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nava Benefits

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🏥 Healthcare

💼 Consulting

📦 Logistics

🔥 Funding within the last year

💰 $30M Series C - Nava on 2025-10

Healthcare • Consulting • Logistics

Nava Benefits is a modern employee benefits broker that pairs elite benefits advisors with an AI-powered SaaS platform (HQ) to simplify benefits administration, streamline renewals, and provide 24/7 support to employees and their families. The company helps HR teams save time, lower healthcare costs, centralize benefits documents, run audits and benchmarking, and offer AI-driven, self-serve member support and plan decision tools. Nava emphasizes alternative health plan strategies (self-funding, PBMs, captives) and positions itself as a tech-enabled extension of HR.

📋 Description

• Own ingestion of external health and benefits data into Nava’s domain models • Build pipelines that fail loudly on bad input, reconcile source counts to normalized tables, and surface issues early • Unify employee eligibility and elections data under consistent mapping, validation, and testing practices • Scale pipeline processes to approximately 40× the current data footprint • Evaluate OLAP versus OLTP storage and event streaming versus nightly jobs • Make member-ID, eligibility, and claims mapping and identity decisions logged and reviewable • Build observability and automation tooling, including TypeScript web applications and AI-assisted matching • Operate pipelines as production software with alerts, idempotent reruns, backfills, and secure handling of SSNs and health information • Participate in interviews involving pipeline experience, bad inbound data, hands-on coding, design, and accomplishments

🎯 Requirements

• Hands-on ownership of a production data pipeline depended on by other teams • Depth in Python and SQL, including joins, indexes, query plans, query-performance diagnosis, and evaluating fixes • Production experience with a data orchestrator; Dagster preferred, Airflow or Prefect comparable • Postgres or a comparable cloud relational database • Reconciliation, data-quality gates, and trusted tests • Daily AI-assisted development workflow; ability to identify appropriate delegation and incorrect agent output • Care with sensitive data • Clear communication with nontechnical people • Dagster specifically, Spark-scale data, a degree, and a years-of-experience number are not required • Hands-on dbt is a strong plus, not a requirement • Candidates from all backgrounds are encouraged to apply

🏖️ Benefits

• Remote-first work arrangement • Autonomy to thrive • Cutting-edge technology and tooling • Collaborative team environment • Direct access to engineers and leaders making product and platform decisions • Mission-driven work to fix healthcare • Inclusive culture • Preparation notes ahead of each interview step