[Remote] Staff Data Engineer, Data Warehouse
Note: The job is a remote job and is open to candidates in USA. Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape. They are seeking a Staff Data Engineer to design and implement data pipelines, warehouse models, and operational processes that support analytics and evidence generation, ensuring data is accurate, accessible, and actionable.
Responsibilities
- Own data pipeline development. Build and maintain reliable pipelines that ingest, transform, and deliver healthcare data across the organization
- Design warehouse data models. Create scalable schemas and data structures that support analytics, reporting, and evidence generation
- Lead data transformation strategy. Establish frameworks and standards that improve consistency, maintainability, and performance
- Ensure data quality and trust. Implement validation, reconciliation, monitoring, and alerting processes across critical datasets
- Support clinical data integration initiatives. Help incorporate new clinical data sources into the warehouse ecosystem
- Optimize warehouse performance. Improve query efficiency, storage utilization, and processing costs as data volumes grow
- Partner with stakeholders on data requirements. Translate business questions into durable data solutions and trusted datasets
- Improve operational excellence. Develop tooling and processes that increase reliability and reduce manual intervention
- Mentor data engineers and analysts. Share best practices and elevate technical standards across the data organization
Skills
- 8+ years of experience building production data pipelines and warehouse solutions
- Deep expertise in SQL and modern data transformation frameworks and Python
- Experience working with large-scale analytical databases and cloud data platforms
- Strong understanding of data modeling, ETL/ELT design, and data lifecycle management
- Experience supporting business-critical reporting or analytical workloads
- Proven ability to improve data reliability and operational maturity
- Comfortable navigating ambiguity and helping define solutions where requirements are still emerging
- Strong ownership mindset with a focus on building durable systems rather than one-off solutions
- Experience working with healthcare data, claims data, or clinical records
- Familiarity with healthcare interoperability standards such as FHIR or HL7
- Experience supporting machine learning or LLM-enabled data workflows
Benefits
- Competitive compensation, including equity
- Full health, dental, and vision coverage
- Retirement savings plan through 401(k)
- Flexible time off
- Opportunities for company-wide connection and events
Company Overview