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Director, Data Product Engineering

Natera · US Remote · Remote

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About Natera

Dedicated to oncology, women’s health, and organ health. Natera’s cell-free DNA tests help protect health and inform more personalized decisions about care. Backed by Lightspeed and Sequoia.

About the role

Natera is seeking a product engineering leader to build and lead the team that designs, delivers, and operates domain data products and AI-enabled analytical solutions on NDP (Natera Data Platform). You will report to the Head of Data & AI and partner with platform, governance, and product functions to turn data needs into certified, production-grade data and analytics products.

What they're looking for

  • 10+ years in data engineering, 5+ leading data or analytics engineering teams at Director level
  • Hands-on depth: you write and review Python and SQL, critique dbt models, debug pipeline failures, and make architecture calls yourself
  • Shipped data products to production with measurable adoption. You can name the products, who used them, and what changed
  • Regulated-environment delivery (healthcare, life sciences, diagnostics, pharma) with PHI and real HIPAA compliance experience
  • Modern data stack: Snowflake, AWS, Claude, dbt, Fivetran, Sigma, orchestrator such as Airflow or Dagster, CI/CD for data pipelines and infrastructure as code
  • Working knowledge of data mesh and headless, domain-owned data products built for human and AI consumers
More about this role

Natera is seeking a product engineering leader to build and lead the team that designs, delivers, and operates domain data products and AI-enabled analytical solutions on NDP (Natera Data Platform). You will report to the Head of Data & AI and partner with platform, governance, and product functions to turn data needs into certified, production-grade data and analytics products.

Natera follows a data mesh architecture with headless data products: domain-owned assets, not tied to any BI layer, built for both human and AI consumption . A data product is ready when it is semantically correct and AI-ready, not just numerically accurate. Your mandate is to make that standard repeatable across every domain while transforming how the team works: AI-native, 3–5x more productive, and self-service for the business.

Please note that this is role focuses on product side of data engineering (not platform). This person needs to demonstrate their ability to

(a) Build a self-service analytics product experience for business users and

(b) Create a catalog of AI ready gold-standard cross functional data products

(c) Create an operating model focusing on reusability, speed. and business value of...

Read the full posting on Natera's site ↗

Engineering Data & AI

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