Staff Data Engineer, Data Warehouse

Pivotal Health•,

13d•$200,000 - $230,000•Hybrid

About The Position

Pivotal Health is building a clinical data platform to generate stronger evidence on behalf of providers. As our data footprint grows, we need dedicated data engineering leadership to build reliable pipelines, trusted datasets, and scalable warehouse infrastructure. This role exists to ensure that data becomes a strategic asset rather than a collection of disconnected systems. As a Staff Data Engineer, you will help design and implement data pipelines, warehouse models, transformation frameworks, and operational processes that support analytics and evidence generation. You will work closely with software engineers, analytics teams, and business stakeholders to ensure data is accurate, accessible, and actionable. This role is well suited for someone who enjoys turning complex data ecosystems into simple, reliable platforms. You'll have the opportunity to influence both architecture and execution while helping shape how Pivotal leverages healthcare data in the future.

Requirements

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.

Nice To Haves

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.

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.