Senior Data Engineer, Data Foundations

Natera

. Design and build governed Data 360 data products integrating clinical, laboratory, operational, and commercial data .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $125,000 - $156,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building governed data products, with a strong focus on data modeling, validation, and integration across clinical and operational domains. Proficient in SQL, Python, and dbt, with a solid understanding of data governance and AI technologies.

Highest-signal resume keywords

Expert-Level SQLStrong PythonDeep Experience With DbtExperience With SnowflakeData Governance Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingData ValidationProduction Data PipelinesAutomated TestingData Quality EngineeringAnalytical Data ModelingSemantic Layer DevelopmentVersion ControlCI/CDModular Design

Soft Skills

Clear CommunicationMentoringCollaboration

Tools & Technologies

SnowflakeDbtSigmaAI Coding AssistantsAgentic ToolsTerraformCortex Analyst

Industry Keywords

HealthcareLife SciencesGenomic DataData GovernanceData ContractsData LineageTrusted-Dataset CertificationBioinformaticsLIMSSalesforce Integrations

Tech Stack

Tools & technologies

AWSCloudPythonSnowflakeSQLTerraform

About the role

Key responsibilities & impact

Design and build governed Data 360 data products integrating clinical, laboratory, operational, and commercial data
Define and maintain canonical definitions for core business metrics
Own foundational-layer architecture decisions, lead design reviews, and make build-vs-buy and technology decisions
Model structured, semi-structured, laboratory, genomic, third-party, and CRM data
Build semantic layers and certified trusted views for self-service analytics
Use Sigma to publish foundational datasets, governed metrics, and reusable workbook components
Build and maintain tested, documented dbt transformation pipelines on Snowflake
Write production-grade SQL and Python and contribute to shared frameworks, templates, and macros
Lead root-cause analysis of complex data issues and drive durable fixes
Establish standards for naming, modeling, testing, documentation, and certification
Implement data quality checks, data contracts, lineage, and monitoring
Ensure PHI and genomic data handling meets HIPAA, CLIA, security, and governance requirements
Validate every data product against source systems and known-good reports and document validation results
Use AI coding assistants and agentic tools across engineering workflows
Build governed data foundations for accurate and safe LLM and agent querying
Contribute to AI-enabled classification, extraction, retrieval, and agent-ready data products
Define team practices for prompts, agent workflows, AI-assisted testing, review, and compliance guardrails
Collaborate with product, lab operations, engineering, commercial, data platform, and AI platform teams
Mentor engineers through code review, pairing, and design feedback
Represent the team in architecture forums and data governance discussions

Requirements

What you’ll need

6+ years of data or software engineering experience (Senior) or 9+ years (Staff)
Track record of designing and shipping production data models and pipelines at scale
Strong software engineering fundamentals: version control, testing, code review, CI/CD, modular design, and maintainable, well-documented code
Expert-level SQL and strong Python
Deep, hands-on experience with dbt or an equivalent transformation framework
Strong grounding in analytical data modeling and experience building semantic layers and governed metric definitions
Experience with a modern cloud data warehouse and cloud infrastructure; Snowflake/AWS preferred
Experience integrating relational, semi-structured, event, operational, and third-party data sources
Experience designing and executing data-product validation, automated tests, and domain-expert verification
Working knowledge of data governance: data contracts, lineage, cataloging, access control, data quality engineering, and trusted-dataset certification
Hands-on daily use of AI coding assistants and agentic tools
Practical experience with AI/LLM technologies, LLM frameworks, managed AI services, or preparing data for LLM and agent consumption
Ability to communicate clearly with technical and non-technical audiences and drive alignment in a matrixed environment
Preferred: Snowflake semantic views, Cortex Analyst, healthcare or life sciences, LIMS, bioinformatics, genomic data, workflow orchestration, Snowflake performance tuning, Terraform, data observability, Salesforce or EHR integrations, Sigma or comparable BI tools
Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience is preferred

Benefits

Comp & perks

Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents
Free testing for employees and immediate families
Fertility care benefits
Pregnancy and baby bonding leave
401k benefits
Commuter benefits
Employee referral program