Staff Data Engineer

Posted Yesterday
Hiring Remotely in United States
Remote
Expert/Leader
Healthtech
The Role
Own the architecture and operation of 9amHealth’s data platform, including Python and SQL ETL/ELT pipelines, AWS infrastructure, Redshift data models, semantic layers, governance, quality, monitoring, and reliability. Establish technical standards, optimize performance and costs, support AI/ML initiatives, build integrations, and mentor data team members. Partner with business and clinical stakeholders to deliver reliable data products and translate complex questions into actionable analytics.
Summary Generated by Built In
About 9amHealth

9amHealth is an AI-enabled virtual specialty care platform focused on managing high-cost chronic conditions at scale. The company partners with employers, health plans, and pharmacy benefit managers to deliver comprehensive, cost-effective medical care for individuals living with obesity, diabetes, hypertension, and dyslipidemia. Members receive access to specialized clinicians, including endocrinologists, obesity medicine specialists, and clinical pharmacists, at-home lab testing, prescription medications, and lifestyle support.
9amHealth was founded in 2021 and is backed by leading healthcare investors like Define Ventures, SemperVirens, 7Wire Ventures, and The Cigna Group Ventures.

About The Role

As a Staff Data Engineer, you'll sit within the data team and report to the VP of Data. You'll own the data platform that powers the business's current data needs and help shape where it goes next.

Our entire data warehouse, ETL, and reporting stack is built in Python on AWS, so deep Python experience is essential. You'll write production-quality Python and SQL, set the architecture and technical standards the team builds on, and stay comfortable working hands-on with AWS services (e.g., Lambda, Glue) and BI tools when needed.


What It Is
  • Define and own the architecture, technical standards, and coding practices for the data platform.

  • Evaluate and recommend data technologies, and contribute to the platform roadmap, including performance and cost optimization.

  • Design, build, and maintain scalable ETL/ELT pipelines in Python using AWS Glue.

  • Drive the analytical data models and semantic layer that power self-service BI and advanced analytics.

  • Build integrations between the data platform and internal or third-party systems, contributing backend code where needed.

  • Set the technical bar for AI-assisted development practices across the data team (GitHub Copilot, Claude, Cursor, or similar).

  • Author, optimize, and maintain complex SQL and database objects (e.g., views, stored procedures) in Redshift.

  • Operate and optimize AWS data infrastructure (e.g., Glue, S3, Redshift, Athena).

  • Own data quality, governance, and reliability for the platform, including monitoring, alerting, and incident response.

  • Support AI/ML initiatives by partnering with data science and ML teams on data prep, feature engineering, and model monitoring.

  • Raise the team's technical standards directly, through code review, architecture decisions, and hands-on mentorship of the data analyst and data engineer.

  • Partner with clinical operations, product, finance, and engineering to translate ambiguous business questions into reliable, well-documented data products.


What You Need
  • 10+ years of professional experience in data engineering or a hybrid data/software engineering role.

  • Strong data or software engineering background: able to write, test, debug, and ship production code independently, using practices like code review and CI/CD.

  • Expert-level Python: deep experience architecting production data pipelines, ETL logic, and reporting systems. Python is our primary language, but we value engineers whose depth extends to other languages relevant to modern data engineering (Java, Scala, Go, etc.) and who can make sound tooling decisions, not just execute in one stack.

  • Expert-level SQL: window functions, CTEs, recursive queries, and query optimization at scale.

  • Hands-on experience with cloud data services, ideally AWS (e.g., Glue, S3, Redshift, Athena), including building and operating production data pipelines on them.

  • Production experience with a cloud data warehouse, ideally Amazon Redshift, including schema design and performance tuning.

  • Experience handling sensitive data, such as PHI, with appropriate access controls and compliance practices.

  • Solid understanding of data modeling techniques: star/snowflake schemas, slowly changing dimensions, event-based models.

  • Demonstrated experience setting technical direction and standards that other engineers and teams build on.

  • Professional use of AI-assisted development tools, with sound judgment on correctness, security, and review.

  • Ability to explain technical trade-offs and risks clearly to both technical and non-technical stakeholders, including executives.


Preferred Qualifications
  • Professional-level cloud certification (e.g., AWS Solutions Architect – Professional, Google Cloud Professional Data Engineer, or Azure Solutions Architect Expert), or equivalent hands-on experience.

  • Experience in health tech, digital health, or another regulated industry.

  • Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar).

  • Background building or contributing to AI/ML features: feature stores, training pipelines, model serving, or RAG architectures.

  • Comfort with infrastructure-as-code (Terraform, CloudFormation) and containerized deployments (Docker, ECS/EKS).

  • Prior experience in a startup or high-growth environment, owning outcomes end to end.

  • A track record of improving developer experience and productivity through tooling, automation, or process improvements, and of influencing engineering practice beyond your immediate team.

  • Experience with orchestration tools and platforms such as Apache Spark, Airflow, or equivalent.

  • Familiarity with BI platforms and semantic layers, such as Looker/LookML, in support of self-service analytics.

What you can expect at 9amHealth

At 9amHealth, you'll join the exciting environment of a startup with the stability of highly experienced founders that have successfully built a business from scratch. We foster a collaborative learning mindset and a passion for improvement. You'll work with a brand-new product alongside a small, flexible team of people eager to shape technology, infrastructure, and culture.

Our team members are spread across the globe, with physical sites in San Diego, California, and Vienna, Austria, but we value your culture regardless of where you work.

Additionally, we provide a professional development budget and support continuing education, empowering our team to grow alongside the company. Team members have the opportunity to make a meaningful impact on chronic disease management and patient outcomes while contributing to a collaborative, mission driven culture focused on improving healthcare accessibility and affordability.

Full-Time/W2 Positions Only: We offer a comprehensive benefits package, including health, dental, and vision insurance, along with flexible PTO and work from home options.

Our commitment to diversity and inclusion

Diabetes disproportionately impacts BIPOC (black, indigenous, and people of color) communities. We are committed to creating a workforce that reflects our patients and creating a positive healthcare experience for them. We welcome applications from people of color, LGBTQ+ individuals, people with disabilities, members of ethnic minorities, and foreign born residents.

Skills Required

  • 10+ years of professional experience in data engineering or a hybrid data/software engineering role
  • Ability to independently write, test, debug, and ship production code using code review and CI/CD practices
  • Expert-level Python experience architecting production data pipelines, ETL logic, and reporting systems
  • Expert-level SQL, including window functions, CTEs, recursive queries, and query optimization at scale
  • Hands-on experience with cloud data services, ideally AWS Glue, S3, Redshift, and Athena
  • Production experience with a cloud data warehouse, ideally Amazon Redshift, including schema design and performance tuning
  • Experience handling sensitive data such as PHI with appropriate access controls and compliance practices
  • Understanding of data modeling techniques including star schemas, snowflake schemas, slowly changing dimensions, and event-based models
  • Experience setting technical direction and standards for other engineers and teams
  • Professional use of AI-assisted development tools with sound judgment regarding correctness, security, and review
  • Ability to communicate technical trade-offs and risks to technical and non-technical stakeholders, including executives
  • Professional-level cloud certification or equivalent hands-on experience
  • Experience in health tech, digital health, or another regulated industry
  • Experience with CI/CD for data assets, such as dbt CI or Great Expectations
  • Experience building or contributing to AI/ML features, including feature stores, training pipelines, model serving, or RAG architectures
  • Experience with infrastructure-as-code and containerized deployments
  • Prior experience in a startup or high-growth environment owning outcomes end to end
  • Track record of improving developer experience and productivity through tooling, automation, or process improvements
  • Experience with orchestration tools such as Apache Spark or Airflow
  • Familiarity with BI platforms and semantic layers such as Looker and LookML

9am.health Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about 9am.health and has not been reviewed or approved by 9am.health.

  • Fair & Transparent Compensation — Pay is considered competitive across multiple job families, with ranges visible on role postings and coverage spanning clinical and non‑clinical positions. Public signals characterize compensation as above market for similar health‑tech firms, albeit directionally.
  • Healthcare Strength — Full‑time roles commonly reference medical, dental, and vision coverage on third‑party listings. This indicates a standard health benefits package is available for eligible employees.
  • Leave & Time Off Breadth — Listings frequently cite around 20 days of vacation or similar PTO for eligible roles. This level of time off is notable for a startup with many remote roles.

9am.health Insights

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The Company
HQ: Encinitas, CA
34 Employees
Year Founded: 2021

What We Do

It’s a new day for diabetes care. 9amHealth is committed to providing compassionate care, affordable medications, and custom healthcare plans to people living with prediabetes and type 2 diabetes. We are dedicated to a care model where you only pay for what you need and have access to medical professionals whenever you need them. Founded in 2021 by the team behind mySugr, 9am offers affordable monthly subscriptions that connect people with a care team of licensed providers, pharmacists, and nutritionists. From at-home lab tests, to speedy prescription delivery, to tools for whole health, 9am offers a wide range of support for every kind of patient—no insurance required. Headquartered in San Diego, 9am is backed by Founders Fund, Define Ventures, Speedinvest and iSeed Ventures.

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