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Data Engineer, Data Warehouse

Job in New York, New York County, New York, 10261, USA
Listing for: Pivotal Health
Full Time position
Listed on 2026-06-19
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Staff Data Engineer, Data Warehouse
Location: New York

About Pivotal Health

Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape.

Today, many providers face persistent underpayment from health insurance companies, despite delivering high-quality care. While processes like IDR (Independent Dispute Resolution) were designed to promote fairness, they’re often administrative-heavy, time-consuming, and difficult to navigate without the right tools.

Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows. We help providers efficiently dispute underpaid claims, reduce administrative burden, and recover the reimbursement they’re entitled to; without adding more work to already stretched teams.

Our full-service IDR solution is just the starting point. We’re building solutions that enable providers to operate with clarity, control, and confidence across the reimbursement journey.

About

The Role

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.

What You’ll Do
  • 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.
Who You Are
  • 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.

This position is not eligible for employer-sponsored work authorization. Applicants must be…

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