Director, Data Product Engineering New US Remote

Natera, Inc.; Northern (KY); Hybrid; USD 187,000 - 233,000; Full time

Benefits offered by this job

Comprehensive medical, dental, vision,

Life and disability coverage

401k benefits

Commuter benefits

Job summary

Natera, Inc. is seeking a product engineering leader to design, deliver, and operate domain data products and AI-enabled analytics on the NDP platform.

You will report to the Head of Data & AI and partner with platform, governance, and product functions to deliver certified, production-grade data and analytics assets. The role emphasizes product-side data engineering, driving self-service analytics, and creating a catalog of AI-ready, gold-standard data products across domains.

Qualifications

• 10+ years in data engineering, 5+ leading data or analytics engineering teams at Director level.
• Hands-on depth: you write and review Python and SQL, critique dbt models, debug pipeline failures, and make architecture calls yourself.
• Shipped data products to production with measurable adoption and impact.
• Regulated-environment delivery (healthcare, life sciences, diagnostics, pharma) with PHI and HIPAA compliance experience.
• Modern data stack: Snowflake, AWS, Claude, dbt, Fivetran, Sigma, orchestrators like Airflow or Dagster; CI/CD for data pipelines and IaC.

Responsibilities

• Own Data Product Delivery across cross-functional data products and analytics experiences.
• Define and enforce publishing standards for analytics products with semantic correctness and AI-readiness.
• Build agentic data engineering capabilities: AI-driven testing, code generation, and data contracts.
• Ensure data products meet quality, observability, and HIPAA/RAQA requirements before shipping.
• Lead the team, review architecture and code, and set engineering standards across tools like Snowflake, AWS, dbt, and Airflow.

Skills

Python

SQL

dbt

Data engineering

AI-assisted development

Tools

Snowflake

AWS

Claude

Sigma

dbt

Fivetran

Airflow

Job description

Natera is seeking a product engineering leader to build and lead the team that designs, delivers, and operates domain data products and AI-enabled analytical solutions on NDP (Natera Data Platform). You will report to the Head of Data & AI and partner with platform, governance, and product functions to turn data needs into certified, production-grade data and analytics products.

Natera follows a data mesh architecture with headless data products: domain-owned assets, not tied to any BI layer, built for both human and AI consumption. A data product is ready when it is semantically correct and AI-ready, not just numerically accurate. Your mandate is to make that standard repeatable across every domain while transforming how the team works: AI-native, 3–5x more productive, and self-service for the business.

Please note that this is role focuses on product side of data engineering (not platform). This person needs to demonstrate their ability to

(a) Build a self-service analytics product experience for business users and

(b) Create a catalog of AI ready gold-standard cross functional data products

(c) Create an operating model focusing on reusability, speed. and business value of data

that scale beyond one business domain.

Critical Priorities for This Role

• Standardize and scale how data products are built — one publishing standard, golden paths, and a common operating model across every domain.
• Make the team AI-native — agentic SDLC and AI-assisted development become how everyone works resulting in higher productivity and growth opportunities
• Deliver a 3–5x productivity gain — instrumented with baselines and delivery KPIs, not anecdotes.
• Raise data product quality — semantically correct, AI-ready, observable, ship-ready data products.
• Make analytics self-service — certified, discoverable products that business users and AI systems consume without an engineering queue.

RESPONSIBILITIES

1. Own Data Product Delivery

• Lead the build of cross functional data products, analytics experiences, and Golden KPI's that are essential to making data driven decisions across the business
• Create the operating model to deliver analytics to business users by leveraging embedded data/AI engineers with each business domain.
• Track and report delivery KPIs: time-to-delivery, certified dataset count, adoption by consuming teams, open production incidents.

2. Standardize & Scale How Data Products Are Built for Analytics and AI use

• Define and enforce the publishing standard for analytics products: semantically correct, AI-ready, lineage documented, ownership assigned, catalog entry complete.
• Establish the headless data product standard: domain-owned assets any authorized consumer — dashboard, workflow, or AI system — can use.
• Build golden paths (templates, examples, documented patterns) so every product starts from a known-good baseline, and make this the operating model for intake, build, certification, and support.

3. Build an AI-Native Engineering Competency

• Drive agentic data engineering as the default: agentic SDLC, AI pipeline generation, agents writing and validating dbt models, AI-driven testing, LLM tools in code review and documentation.
• Train every engineer to work AI-natively and redefine the working model — SDLC steps, roles, human-in-the-loop checkpoints, definition of done.
• Own a measurable plan to lift productivity 3–5x: baseline throughput and cycle time, instrument each change, report outcomes.

4. Raise the Data Product Quality Bar

• Enforce engineering standards on every production solution: CI/CD for pipelines, infrastructure as code, data observability, data quality frameworks.
• Meet HIPAA, RAQA, and data classification requirements at design time. If a product does not meet the bar, it does not ship.

5. Make Data Self-Service for Humans and AI

• Own the NDP contribution and discovery model: what gets published, how it is documented, and how human and AI consumers find and evaluate certified assets.
• Ensure every catalog entry carries semantic metadata and AI-readiness classification so business users and AI agents answer their own questions without an engineering ticket.
• Partner with the Data Governance Lead to embed data contracts, certification review, and access policy into the lifecycle so self-service is safe and correctly scoped.

6. Lead the Team and Set the Technical Bar

• Hire, coach, and grow data and analytics engineers; set clear expectations, give direct feedback, build real career paths.
• Stay hands-on: review architecture and code, debug production failures, and set the standard by example across Snowflake, AWS, Claude, Sigma, dbt, Fivetran, Python, and Airflow.
• Be the engineering face of data products to business stakeholders: translate ambiguous needs into scoped, time-bound commitments; when things change, communicate early with a plan.

WHAT WE’RE LOOKING FOR

Required

• 10+ years in data engineering, 5+ leading data or analytics engineering teams at Director level.
• Hands-on depth: you write and review Python and SQL, critique dbt models, debug pipeline failures, and make architecture calls yourself.
• Shipped data products to production with measurable adoption. You can name the products, who used them, and what changed.
• Regulated-environment delivery (healthcare, life sciences, diagnostics, pharma) with PHI and real HIPAA compliance experience.
• Modern data stack: Snowflake, AWS, Claude, dbt, Fivetran, Sigma, orchestrator such as Airflow or Dagster; CI/CD for data pipelines and infrastructure as code.
• Working knowledge of data mesh and headless, domain-owned data products built for human and AI consumers.
• Built or led teams using AI-assisted development in production: agents, code generation, AI-driven testing and validation.
• Defined engineering standards, golden paths, or operating models that scaled across multiple teams or domains.
• Strong communicator: runs a stakeholder review, writes a technical proposal, represents engineering with executives.

Nice to Have

• Diagnostics, genomics, or clinical data engineering (BAM, VCF, FASTQ).
• Vector databases, embeddings, or RAG architectures in a data engineering context.
• Data contracts as engineering artifacts: schema enforcement, versioning, change management.
• Rolled out enterprise agentic tooling (e.g., Claude Code) to an engineering org, including training and change management.

The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

Remote USA

$186,700 - $233,400 USD

OUR OPPORTUNITY

Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.

The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.

WHAT WE OFFER

Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!

Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.

All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws.

If you are based in California, we encourage you to read this important information for California residents.

Please be advised that Natera will reach out to candidates with a @ natera.com email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Natera’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.