Data Engineering Manager - DSPE Lab Operations

Natera is a global leader in cell-free DNA (cfDNA) precision medicine and genetic diagnostics across oncology, women’s health, and organ health. Our mission is to make personalized genetic testing part of the standard of care to protect health and enable targeted medical interventions.

As the Manager of the Data Engineering & Delivery (DED) team inside our Data Science Production Engineering (DSPE) department, you will lead a specialized engineering team managing petabyte-scale genomics, clinical, and laboratory dataset operations. You will oversee the design, development, and maintenance of cloud data infrastructure, automated ETL pipelines, dbt data models, and BI delivery platforms that power Natera's Lab Operations and Genetic Counselor teams. Operating in a CLIA/FDA regulated environment, you will translate complex clinical requirements into technical specifications, enforce strict data quality standards, and ensure timely data delivery that directly impacts patient medical outcomes.

Key Responsibilities

• Team Leadership & Operational Effectiveness: Lead, mentor, and grow a team of data engineers and delivery specialists; track operational effectiveness, manage delivery timelines, and coach team members on modern cloud data stack best practices.
• Data Pipeline & Architecture Ownership: Direct the development and maintenance of scalable data ingestion infrastructure, petabyte-scale ETL/ELT pipelines, and automated delivery systems for production and internal DSPE applications.
• System Design & Technical Architecture: Partner with DSPE leadership to create system design documentation, data model schemas, and data warehouse architectures that scale efficiently.
• Quality, Regulatory & Compliance Management: Improve and enforce operating procedures for data accuracy, testing, validation, and documentation in compliance with CLIA, FDA, and HIPAA regulatory guidelines.
• Hands-On Engineering Contribution: Contribute directly to key development, testing, deployment, code reviews, and validation tasks using SQL, Python, Git, and dbt.
• Cross-Functional Alignment: Engage directly with internal stakeholders—including Bioinformatics, Lab Operations, Clinical Analytics, and Genetic Counselors—to align product roadmaps, manage dependencies, and exchange performance metrics.

Requirements

Engineering Management & Clinical Data Depth

• Education: Master’s degree (or Doctorate) in Data Science, Statistics, Bioinformatics, Computer Science, Mathematics, or a related quantitative field.
• Industry Experience:
  • Master’s Degree Holders: Minimum 5+ years of relevant industry experience in data engineering, data science, or analytics engineering.
  • Doctorate Degree Holders: Minimum 2+ years of relevant industry experience.
• People Management: Minimum 2+ years of direct management experience leading a Data Engineering, Data Delivery, or Data Analytics team.
• Regulated Environment Background: Minimum 2+ years of working experience in a highly regulated clinical/life sciences environment (e.g., CLIA, CAP, or FDA compliant settings).
• Core Technical Stack:
  • Expert proficiency in SQL (complex queries, window functions, aggregation across multi-terabyte/petabyte databases) and Python.
  • Proven expertise building data transformation pipelines, data QC frameworks, and data modeling tools (e.g., dbt).
  • Proficiency with version control workflows (Git, GitHub, GitLab) and BI visualization platforms (Tableau, Power BI, AWS QuickSight).
• Bioinformatics & Health Data: Working knowledge of genomics workflows, bioinformatics pipelines, electronic health records (EHR), or clinical health data standards.

Work Logistics

• Ability to work remotely within the United States.

Preferred Qualifications

• Ph.D. in Bioinformatics, Human Genetics, Computational Biology, or Computer Science.
• Hands-on experience developing data pipelines with dbt (data build tool) in modern cloud data warehouses (Snowflake, AWS Redshift, Databricks).
• Deep knowledge of human genetics, cell-free DNA (cfDNA) testing, or clinical oncology workflows.
• Experience with R programming for statistical analysis and clinical data validation.

Total Rewards & Benefits

• Compensation: Base salary range of $127,200 – $159,000 USD benchmarked by role and geographic location.
• Healthcare & Wellness: Comprehensive medical, dental, vision, life, and disability plans for eligible employees and dependents.
• Family & Health Perks: Free genetic testing for employees and immediate family, fertility care benefits, paid pregnancy leave, and baby bonding leave.
• Retirement & Transportation: 401(k) retirement savings plan, pretax commuter benefits, and a generous employee referral incentive program.