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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.