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.
Washington, District of Columbia, USA
Live, first seen by us 25 days agoLocation Remote. Must be based in the United States and authorized to work without sponsorship.
Location type: RemoteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Product & EngineeringFrom the employer’s posting
Must be based in the United States and authorized to work without sponsorship
Design, build and maintain scalable ETL pipelines and data models
Develop data integration workflows between internal systems and external sources
Optimize and scale cloud-hosted databases for complex healthcare datasets
Ensure data security and compliance with healthcare standards such as HIPAA and HITRUST
Create documentation and monitoring to keep data reliable and transparent
Design, build, and maintain scalable ETL pipelines and data models
Develop robust data integration workflows, enabling seamless data exchange between internal systems and external data sources.
Optimize and scale cloud-hosted databases and data infrastructure to handle complex healthcare datasets efficiently.
Ensure data security and compliance with healthcare industry standards (e.g., HIPAA, HITRUST).
Create documentation and implement monitoring solutions to ensure data reliability and transparency.
7+ years of experience as a data engineer or similar role, with at least several years of experience in health tech.
Strong expertise in SQL and Python.
Hands-on experience with modern data warehousing technologies (e.g., Snowflake, BigQuery, Redshift).
Experience with data pipeline and workflow orchestration tools (e.g., Temporal, Airflow, Prefect, Dagster).
Experience with cloud platforms such as AWS (preferred), GCP, or Azure.
Solid understanding of data security principles and familiarity with healthcare data compliance requirements.
Experience with DBT for data transformation and modeling.
Experience with claims data sharing formats (e.g., 837, 834, CCLF) and modeling clinical quality measures (e.g., CQL).
Ownership: We follow through with integrity and hold ourselves to high standards.
Experience with lightweight, cloud-hosted secure data transfer solutions such as SFTPGo.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$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.
Day 25
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
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- 7+ years of experience as a data engineer or similar role, with at least several years of experience in health tech. - Strong expertise in SQL and Python. - Hands-on experience with modern data warehousing technologies (e.g., Snowflake, BigQuery, Redshift).
- Experience with data pipeline and workflow orchestration tools (e.g., Temporal, Airflow, Prefect, Dagster). - Experience with cloud platforms such as AWS (preferred), GCP, or Azure. - Solid understanding of data security principles and familiarity with healthcare data compliance requirements.
- Strong expertise in SQL and Python. - Hands-on experience with modern data warehousing technologies (e.g., Snowflake, BigQuery, Redshift). - Experience with data pipeline and workflow orchestration tools (e.g., Temporal, Airflow, Prefect, Dagster).
Preferred Experience: - Experience with DBT for data transformation and modeling. - Experience with lightweight, cloud-hosted secure data transfer solutions such as SFTPGo.
- Hands-on experience with modern data warehousing technologies (e.g., Snowflake, BigQuery, Redshift). - Experience with data pipeline and workflow orchestration tools (e.g., Temporal, Airflow, Prefect, Dagster). - Experience with cloud platforms such as AWS (preferred), GCP, or Azure.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
About Chamber:
Cardiovascular disease remains the leading cause of death in America. At Chamber, we are rebuilding the system for cardiology, creating a world where outcomes, not volume, define success. We partner with independent cardiologists to help them lead population health efforts in their communities, equipping them with technology, data, and operational tools that turn complex insights into better care for patients.
Our model blends clinical expertise, thoughtful design, and a modern operating platform that supports physicians, patients, and payers alike. We believe innovation and empathy go hand in hand, and by combining cutting-edge AI tools with a relentless focus on human care, we can transform heart health at scale.
Job Overview:
We are seeking a Staff-level Data Engineer who is passionate about creating scalable, secure, and efficient data systems. You will play a pivotal role in designing and implementing the data architecture that powers our core products, which provide actionable insights to cardiologists, care teams, and patients. The ideal candidate combines deep technical expertise with an eagerness to collaborate and innovate within a fast-paced, early-stage health tech environment.
Key Responsibilities:
Design, build, and maintain scalable ETL pipelines and data models to support our analytics and product needs.
Develop robust data integration workflows, enabling seamless data exchange between internal systems and external data sources.
Optimize and scale cloud-hosted databases and data infrastructure to handle complex healthcare datasets efficiently.
Ensure data security and compliance with healthcare industry standards (e.g., HIPAA, HITRUST).
Collaborate with product, engineering, and clinical teams to define and implement data requirements.
Create documentation and implement monitoring solutions to ensure data reliability and transparency.
Required Qualifications:
7+ years of experience as a data engineer or similar role, with at least several years of experience in health tech.
Strong expertise in SQL and Python.
Hands-on experience with modern data warehousing technologies (e.g., Snowflake, BigQuery, Redshift).
Experience with data pipeline and workflow orchestration tools (e.g., Temporal, Airflow, Prefect, Dagster).
Experience with cloud platforms such as AWS (preferred), GCP, or Azure.
Solid understanding of data security principles and familiarity with healthcare data compliance requirements.
Experience with AI software development tools (e.g., Claude Code, Cursor) and an AI forward mindset
Demonstrated ability to work with messy, complex data and transform it into actionable insights.
Strong communication skills and the ability to work effectively in cross-functional teams.
Preferred Experience:
Experience with DBT for data transformation and modeling.
Experience with lightweight, cloud-hosted secure data transfer solutions such as SFTPGo.
Experience with healthcare interoperability standards such as FHIR and HL7 event formats.
Nice to Have:
Experience with claims data sharing formats (e.g., 837, 834, CCLF) and modeling clinical quality measures (e.g., CQL).
Experience working with the Tuva Project.
Understanding of common clinical quality measure definitions and rules engine logic.
Our values guide how we lead, collaborate, and care:
Low Ego: We stay grounded, curious, and open to feedback.
Empathy: We build trust through compassion and thoughtful communication.
Courage: We take action, think critically, and challenge ideas respectfully.
Ownership: We follow through with integrity and hold ourselves to high standards.
Grit: We push through ambiguity, move with urgency, and solve problems with horsepower and heart.
Remote. Must be based in the United States and authorized to work without sponsorship.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Washington, District of Columbia, USA
Location Remote. Must be based in the United States and authorized to work without sponsorship.
Location Remote. Must be based in the United States and authorized to work without sponsorship.