Director of Data Production Engineering & Delivery

Natera, Inc.; San Carlos, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Natera, Inc. seeks a Manager of Data Science Production Engineering to lead the Data Engineering & Delivery (DED) team within DSPE. You will guide data infrastructure, ingestion, ETL pipelines, and data delivery solutions, supporting Lab Operations and Clinical teams with robust, scalable data products and automation.

Ideal candidates have strong SQL/Python, regulatory experience, and proven leadership, with a focus on delivering accurate data at scale across diverse data sources.

Qualifications

• Advanced SQL and Python skills with data engineering focus.
• Experience in regulated environments (CLIA/FDA) is preferred.
• Proven leadership of Data Engineering/Delivery teams.
• Strong communication and cross-functional collaboration.

Responsibilities

• Lead a Data Engineering & Delivery team to build data infrastructure and ETL pipelines for production and internal DSPE apps.
• Translate business needs into technical specs and implementation plans.
• Create design docs for data systems and ensure robust delivery.
• Contribute to development, testing, deployment, and maintenance activities.

Skills

SQL

Python

R

Data visualization

Statistical techniques

Data products

Git workflow

Communication

Problem solving

Team leadership

Education

Master's degree in Statistics, Data Science, Bioinformatics, CS, Math, OR, etc.

Doctorate is a plus

Tools

Tableau

Power BI

AWS QuickSight

dbt

GitHub

GitLab

Job description

Natera, Inc. seeks a Manager of Data Science Production Engineering to lead the Data Engineering & Delivery (DED) team within DSPE. You will guide data infrastructure, ingestion, ETL pipelines, and data delivery solutions, supporting Lab Operations and Clinical teams with robust, scalable data products and automation.

Ideal candidates have strong SQL/Python, regulatory experience, and proven leadership, with a focus on delivering accurate data at scale across diverse data sources.