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Pivotal Health is a technology platform helping healthcare providers navigate complex reimbursement landscapes and recover underpaid claims through an AI-driven, full-service solution. The company combines software, data, and service to simplify workflows around Independent Dispute Resolution (IDR) and broader reimbursement operations.
As Head of Data Engineering, you will own the platform, architecture, and team powering Pivotal's end-to-end data infrastructure. This is a systems-focused leadership role treating data engineering as a specialized software engineering discipline—emphasizing CI/CD, maintainability, scalability, and code quality over traditional GUI tools.
Key responsibilities include: evolving and modernizing the existing data infrastructure using modern, code-driven patterns and cloud-native tools; building and leading a high-caliber team of software engineers specializing in data pipelines and processing; providing infrastructure, streaming/batch frameworks, and APIs so product teams can own their domain models; owning the complete data lifecycle from ingestion through consumption; promoting rigorous software engineering practices including automated testing, infrastructure-as-code, and observability; and implementing security and compliance controls for sensitive healthcare data.
You will serve product, engineering, AI, and business intelligence teams as primary customers, building the platform rather than owning schemas. The role requires deep hands-on involvement—you must stay close enough to technology to earn respect from senior engineers while making architectural trade-off decisions.
Ideal candidates bring 10+ years in software or data infrastructure with proven experience inheriting and evolving existing platform architectures. You should have deep experience with modern, code-first data architectures including event streaming, distributed processing, modern lakehouses, and containerized orchestration. Understanding that schema and domain model ownership belongs to engineering teams, you excel at building internal tools and APIs that make data publishing and consumption frictionless.
Extra credit for experience with real-time/event-driven healthcare or financial data streams (claims, clinical data, transactions); background in HealthTech, FinTech, or regulated industries handling sensitive data; building data platforms optimized for LLMs and production ML pipelines; and familiarity with HIPAA, PHI, and zero-trust security patterns.
