Natera
Natera
Natera develops cell-free DNA testing and bioinformatics solutions for healthcare. Its diagnostic technologies support non-invasive prenatal screening, cancer detection, and organ transplant monitoring, helping clinicians and patients access genetic insights for more informed care decisions. The company’s work brings together biotechnology, data analysis, and clinical applications across several areas of modern medicine.

Director of Data Product Engineering at Natera – United States Remote

Lead data products and AI-enabled analytics at Natera, a global cell-free DNA testing company. Build self-service, HIPAA-compliant data solutions across business domains.

Description

  • Lead the team that designs, delivers, and operates domain data products and AI-enabled analytics on the Natera Data Platform.
  • Oversee cross-functional data products, analytics experiences, and Golden KPIs.
  • Develop an operating model that embeds data and AI engineers within business domains.
  • Measure and communicate delivery performance through time to delivery, certified datasets, adoption, and production incidents.
  • Set and uphold publishing standards for analytics products.
  • Define standards for headless data products and create reusable golden paths.
  • Advance agentic data engineering, AI-assisted development, automated testing, and AI-supported code review and documentation.
  • Train engineers in AI-native workflows to improve productivity by 3–5x.
  • Maintain standards for CI/CD, infrastructure as code, data observability, and data quality.
  • Deploy automated drift detection, root-cause analysis, and human-in-the-loop recovery processes.
  • Maintain compliance with HIPAA, RAQA, and data classification requirements.
  • Own the NDP contribution and discovery model while enabling self-service data consumption.
  • Work with the Data Governance Lead on data contracts, certification reviews, and access policies.
  • Recruit, mentor, and develop data and analytics engineers.
  • Review architecture and code, troubleshoot production failures, and establish technical standards across Snowflake, AWS, Claude, Sigma, dbt, Fivetran, Python, and Airflow.
  • Convert business needs into defined commitments and keep stakeholders informed of changes.

Requirements

  • At least 10 years of experience in data engineering.
  • At least five years leading data or analytics engineering teams at the Director level.
  • Hands-on experience with Python and SQL.
  • Ability to evaluate dbt models, troubleshoot pipeline failures, and make architecture decisions.
  • Experience delivering production data products with measurable adoption.
  • Experience delivering in regulated healthcare, life sciences, diagnostics, or pharmaceutical environments.
  • Practical experience handling PHI and meeting HIPAA requirements.
  • Experience with Snowflake, AWS, Claude, dbt, Fivetran, Sigma, and Airflow or Dagster.
  • Experience implementing CI/CD for data pipelines and infrastructure as code.
  • Working knowledge of data mesh and headless, domain-owned data products.
  • Experience leading teams that use AI-assisted development in production.
  • Experience establishing engineering standards, golden paths, or operating models across multiple teams or domains.
  • Strong stakeholder management, technical writing, and executive communication skills.

Benefits

  • Comprehensive medical, dental, vision, life, and disability coverage for eligible employees and dependents.
  • Complimentary testing for employees and their immediate families.
  • Fertility care benefits.
  • Pregnancy and baby bonding leave.
  • 401(k) benefits.
  • Commuter benefits.
  • Employee referral program.

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