Chamber
Chamber
Chamber is a healthcare technology company serving cardiology teams in the transition to value-based care. Its SaaS tools and support services provide real-time insights, administrative assistance, and payer-negotiation expertise to help practices coordinate comprehensive care and identify new revenue opportunities without adding direct costs for the practice. By connecting cardiologists with hospital systems and a broader network of high-performing providers, Chamber supports a more effective cardiology care ecosystem and helps practices align reimbursement with timely, appropriate treatment.

Staff Data Engineer (Remote, United States)

Lead the design of scalable ETL pipelines, integrations, and cloud data infrastructure for Chamber’s cardiology platform. Build secure, compliant healthcare data systems that support analytics and product development.

Description

  • Build and maintain scalable ETL pipelines and data models for analytics and product use cases
  • Develop reliable workflows that connect internal systems with external data sources
  • Scale and optimize cloud databases and infrastructure for complex healthcare datasets
  • Protect data and uphold healthcare compliance requirements, including HIPAA and HITRUST
  • Partner with product, engineering, and clinical teams to define and deliver data capabilities
  • Document systems and establish monitoring to improve data reliability and visibility

Requirements

  • At least 7 years of experience in data engineering or a comparable role, including several years in health technology
  • Advanced proficiency in SQL and Python
  • Practical experience with modern data warehouses such as Snowflake, BigQuery, or Redshift
  • Experience using pipeline and workflow orchestration tools such as Temporal, Airflow, Prefect, or Dagster
  • Experience with AWS, preferably, or with GCP or Azure
  • Understanding of data security principles and healthcare compliance requirements
  • Experience with AI development tools such as Claude Code or Cursor, along with an AI-forward approach
  • Ability to turn messy, complex datasets into actionable insights
  • Strong communication skills and effectiveness in cross-functional collaboration
  • Based in the United States and authorized to work without sponsorship

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