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Staff Data Engineer

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Remote — work setting source
Location type: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data — team source

Before you apply

Sponsorship
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What you’ll work on

Full posting

As a Staff Data Engineer, you'll sit within the data team and report to the VP of Data.

Our entire data warehouse, ETL, and reporting stack is built in Python on AWS, so deep Python experience is essential.

  • Define and own data platform architecture, technical standards and coding practices

  • Design, build and maintain Python ETL/ELT pipelines on AWS Glue

  • Drive analytical data models and the semantic layer for BI and analytics

  • Write and optimize complex SQL and database objects in Redshift

  • Own data quality, governance and reliability, including monitoring and incident response

From the employer’s posting
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.
Define and own the architecture, technical standards, and coding practices for the data platform.
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.
Author, optimize, and maintain complex SQL and database objects (e.g., views, stored procedures) in Redshift.
Own data quality, governance, and reliability for the platform, including monitoring, alerting, and incident response.

What you’ll bring

All qualifications

Core experience

  • 10+ years of professional experience in data engineering or a hybrid data/software engineering role.
  • 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.
  • Hands-on experience with cloud data services, ideally AWS (e.g., Glue, S3, Redshift, Athena), including building and operating production data pipelines on them.
  • 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.

Preferred experience

  • Experience in health tech, digital health, or another regulated industry.
  • Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar).
  • Prior experience in a startup or high-growth environment, owning outcomes end to end.
  • Experience with orchestration tools and platforms such as Apache Spark, Airflow, or equivalent.
Qualification wording
10+ years of professional experience in data engineering or a hybrid data/software engineering role.
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.
Hands-on experience with cloud data services, ideally AWS (e.g., Glue, S3, Redshift, Athena), including building and operating production data pipelines on them.
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.
Experience in health tech, digital health, or another regulated industry.
Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar).
Prior experience in a startup or high-growth environment, owning outcomes end to end.
Experience with orchestration tools and platforms such as Apache Spark, Airflow, or equivalent.

About 9amHealth

9amHealth is an AI-enabled virtual specialty care platform focused on managing high-cost chronic conditions at scale.

In the employer’s words · Read in context · Company website ↗

Apply at 9amHealth

Posting record

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Status in our records
Live
First seen by us
Oct 30, 20265 days ago
Recorded sightings
6
Last seen by us
Nov 4, 2026
Reposted
once since Jun 2, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 5

Similar jobs usually come down between day 5 and day 54.

From 10,703 similar postings that came down. Coming down is not always a hire.

9amHealth is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • 50% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • Scala
  • SQL
  • AWS
  • Azure
  • dbt
  • Docker
  • Looker
  • Redshift
  • S3
  • Spark
  • Terraform
  • Airflow
  • Go
  • GCP
Where the posting names them
- 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.
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
- 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.
- 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).
- 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.
- 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.
- 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.
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 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.
- 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.
- 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
- 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.
- 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.

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Has 9amHealth posted this job before?

Yes. We’ve followed one other Staff Data Engineer job there since June 2026. It came down after 149 days.

  1. Place not statedCame down after 149 days, first seen Jun 2
  2. This jobUp 5 days so far, first seen Oct 30

Job description

View original posting ↗

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.

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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.
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