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Sr. Software Engineer/Tech Lead, Data & AI Engineering

Natera· Engineering Data & AI
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Remote$150.4k - $188kFull-timePosted 6mo ago

About the role

Senior data & AI engineering leadership role focused on building analytics and AI solutions for business stakeholders within a regulated environment. Hands-on contributor responsible for architecture, design, implementation, and mentorship, with an emphasis on AI-native practices, data quality, privacy, and compliance.

Responsibilities

  • Own the technical design and architecture for the analytics and AI solutions your team delivers; drive design reviews and make build-vs-buy and technology decisions in partnership with the data platform and architecture teams.
  • Translate business stakeholder needs into well-scoped technical designs, breaking down complex analytics initiatives into deliverable milestones for the team.
  • Establish and enforce engineering standards for modeling, pipeline design, testing, CI/CD, and observability so solutions are built consistently and reusably across business domains.
  • Design, build, and maintain scalable data pipelines and transformations on our cloud data platform, sourcing clinical, laboratory, operational, and commercial data to serve business analytics.
  • Develop governed data models and semantic layers that power self-service analytics, dashboards, and data products (e.g., Patient 360, Provider 360, Test 360) for business teams.
  • Develop AI solutions to enable business productivity and automation through agentic workflows, RAG/retrieval, and LLM pipelines (extraction/classification)
  • Write production-grade SQL and Python; contribute to shared frameworks, templates, and tooling that let the team deliver new analytics solutions faster.
  • Ensure the data layer supports performant, trustworthy analytics and LLM querying; lead root-cause analysis on complex data issues and drive durable fixes.
  • Use AI coding assistants and agentic tools daily across the development lifecycle—design, coding, testing, documentation, and operations—and measurably increase your own and the team’s throughput.
  • Define and scale the team’s AI-native engineering practices: prompt and context patterns, reusable agent workflows, AI-assisted testing and review, and the guardrails that keep quality and compliance intact.
  • Mentor and grow engineers through code review, pairing, and design coaching; partner with the engineering manager on technical hiring, onboarding, and skills development.
  • Implement data quality checks, contracts, lineage, and monitoring so that downstream consumers can trust the data by default.
  • Own operational excellence for the team’s solutions: SLAs, incident response, and cost efficiency of compute and storage.
  • Ensure pipelines handling PHI and genomic data meet HIPAA, CLIA, and internal security and governance requirements, including access controls, auditability, and retention.
  • Work directly with business stakeholders across functions to understand their questions, shape analytics solutions to their needs, and communicate technical tradeoffs in plain language.
  • Collaborate with data platforms and AI platform teams to ensure solutions build on shared foundations rather than one-off pipelines.
  • Represent the team in architecture forums, data governance discussions, and tool evaluations.

Qualifications

  • 7+ years of data or software engineering experience, including 2+ years leading technical design and delivery for a team or major workstream, ideally building analytics solutions for business users.
  • Demonstrated ability to mentor engineers, run effective design and code reviews, drive technical consensus, and communicate clearly with technical and non-technical audiences.
  • Demonstrated, hands-on use of AI coding assistants and agentic tools in daily engineering work, with a point of view on how to use them well.
  • Expert-level SQL and strong Python, with a track record of shipping and operating production data pipelines and data models at scale.
  • Deep experience with a modern cloud data warehouse and cloud infrastructure (Snowflake/AWS preferred).
  • Hands-on experience with transformation frameworks (dbt or equivalent) and workflow orchestration (Airflow, Dagster, Prefect, or similar).
  • 1-2 years of practical background building with LLM frameworks (LangChain, LangGraph, or equivalent) alongside managed AI services and model routing gateways like Snowflake Cortex, AWS Bedrock, and foundational APIs.
  • Strong grounding in analytical data modeling (dimensional or domain-driven), semantic layers, data quality engineering, and CI/CD for data systems.

Skills

Required:SQLPythonCloud data warehouse (Snowflake)dbt or equivalentAirflow/Ddagster/PrefectLLM frameworks (LangChain, LangGraph)AI-native / agentic tooling

Benefits

  • Competitive Benefits - comprehensive medical, dental, vision, life and disability plans for eligible employees and dependents; free testing for employees and immediate families; fertility care benefits; pregnancy and baby bonding leave; 401k benefits; commuter benefits; and more; generous employee referral program.
Last updated Oct 1, 2026. Interested? Apply on the company site.

About Natera

A global leader in cfDNA testing

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.

oncologywomen's healthorgan healthcell-free DNA
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