Staff Data Engineer, Data Warehouse

Hybrid

Responsibilities

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.
Improve query efficiency, storage utilization, and processing costs as data volumes grow. - Partner with stakeholders on data requirements.
Develop tooling and processes that increase reliability and reduce manual intervention. - Mentor data engineers and analysts.

Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows.
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
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.