Senior Data Engineer, Data Foundations

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop governed Data 360 data products that incorporate clinical, laboratory, operational, and commercial data.

• Establish and uphold canonical definitions for essential business metrics.

• Take ownership of foundational-layer architecture decisions and spearhead design reviews.

• Model structured, semi-structured, laboratory, genomic, third-party, and CRM data.

• Construct semantic layers and certified trusted views for self-service analytics.

• Publish foundational datasets, governed metrics, and reusable workbook components utilizing Sigma.

• Develop and sustain tested, documented dbt transformation pipelines on Snowflake.

• Write production-grade SQL and Python, contributing to shared frameworks, templates, and macros.

• Conduct root-cause analysis of complex data problems and implement lasting solutions.

• Set standards for naming, modeling, testing, documentation, and data certification.

• Implement data quality checks, data contracts, lineage, and monitoring procedures.

• Ensure compliance with HIPAA, CLIA, security, and governance requirements for PHI and genomic data handling.

• Collaborate with governance, security, and data platform teams regarding metadata and discoverability.

• Validate data products against source systems and known-good reports, documenting verification outcomes.

• Utilize AI coding assistants and agentic tools throughout design, coding, testing, documentation, and operations.

• Establish governed data foundations for accurate and secure LLM and agent querying.

• Contribute to AI-enabled classification, extraction, retrieval, and agent-ready data products.

• Assist in defining AI engineering practices, workflows, testing, reviews, and guardrails.

• Work closely with product, lab operations, engineering, commercial, data platform, and AI platform teams.

• Mentor engineers through code reviews, pairing sessions, and design feedback.

⛳️ Requirements

• Minimum of 6 years of data or software engineering experience for Senior role or 9 years for Staff role.

• Proven track record in designing and delivering production data models and pipelines at scale.

• Strong fundamentals in software engineering, including version control, testing, code review, CI/CD, modular design, and maintainable, well-documented code.

• Expertise in SQL and proficiency in Python.

• Extensive hands-on experience with dbt or a similar transformation framework.

• Solid knowledge in analytical data modeling and experience in building semantic layers and governed metric definitions.

• Familiarity with a modern cloud data warehouse and cloud infrastructure; Snowflake/AWS is preferred.

• Experience in integrating relational, semi-structured, event, operational, and third-party data sources.

• Knowledge in defining and applying data standards.

• Background in designing and executing data-product validation, automated tests, and source-system reconciliation.

• Understanding of data governance practices, including data contracts, lineage, cataloging, access control, data quality engineering, and dataset certification.

• Hands-on experience with AI coding assistants and agentic tools.

• Practical experience with AI/LLM technologies or preparing data for LLM and agent consumption.

• Ability to communicate effectively with both technical and non-technical audiences and foster alignment in a matrixed environment.

• Preferred: experience with Snowflake semantic views, Cortex Analyst, healthcare or life sciences, LIMS, bioinformatics, genomic data, workflow orchestration, Snowflake tuning, Terraform, Salesforce or EHR data, Sigma or comparable BI tools.

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience is preferred.

🏝️ Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents.

• Free testing for Natera employees and their immediate families.

• Fertility care benefits.

• Pregnancy and baby bonding leave.

• 401k benefits.

• Commuter benefits.

• Employee referral program.

• Opportunities for professional growth.