Senior Data Engineer

Verantos
$150,000 - $220,000Remote

About The Position

The data that powers Verantos's evidence platform comes from real-world clinical systems — messy, inconsistent, and constantly changing. We need a Senior Data Engineer who knows how to build pipelines that handle that chaos gracefully, not one who fights fires every time something unexpected arrives. This is a senior role on the team responsible for shipping our data product every quarter. You will set the technical direction for how we ingest, transform, and quality-check data at scale, with an eye toward systems that run themselves. Just as important is the ability to think beyond the pipeline: the best candidate understands what the data means to the researchers who depend on it, and brings that perspective into the engineering decisions they make. This is a fully remote, US-based role.

Requirements

  • 8+ years in data engineering, with experience at a technical lead level.
  • Production experience with Snowflake and dbt as primary data platform tools.
  • Strong Python skills for building and maintaining data pipelines.
  • Has built resilient pipelines on irregular, high-variance data sources and knows what it takes to keep them running without babysitting.
  • Thinks in systems: designs for observability, failure recovery, and automation.
  • Can engage meaningfully with the business and domain context around the data, not just the engineering.
  • Uses AI tools actively in their own work and is curious about applying them within the pipeline, particularly for data quality monitoring and anomaly detection at scale.
  • Communicates clearly and works well across engineering, product, and clinical stakeholders.

Nice To Haves

  • Familiarity with OMOP CDM — not required, but it matters here more than most places.
  • Experience with EHR data or other clinical datasets.
  • Familiarity with other healthcare data standards such as HL7 or FHIR.
  • Experience with data observability tooling in production environments.

Responsibilities

  • Lead the design and evolution of the data platform architecture, establishing patterns and standards the team builds on.
  • Build and operate production-grade data pipelines that ingest and transform high-variance, real-world clinical data reliably and at scale.
  • Design for automation from the start: pipelines that detect problems, recover gracefully, and surface issues without requiring manual intervention to run.
  • Contribute to quarterly data product releases, working closely with product, clinical, customer success teams to meet commitments.
  • Build data quality tests that reflect the evolving needs of our downstream consumers.
  • Mentor and elevate other data engineers through code review, architecture decisions, and shared standards.
  • Actively use and advocate for AI tools that improve the team's development velocity and code quality.
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