Head of Data Engineering
About The Position
Pivotal Health is seeking a Head of Data Engineering to lead the platform, architecture, and team responsible for their end-to-end data infrastructure. This role views data engineering as a specialized discipline of Software Engineering, emphasizing systems-minded leadership with strong software engineering fundamentals. The ideal candidate will treat data infrastructure with the same rigor as core backend services, focusing on CI/CD, maintainability, scalability, and code quality. The Head of Data Engineering will inherit an existing data foundation and guide its evolution into a modern, distributed, high-throughput platform, considering the entire data lifecycle from ingestion to consumption. A key aspect of this role is building the platform and tools that empower the entire software engineering organization to own their schemas, publish clean data, and consume platform services seamlessly, rather than siloing data modeling within the data engineering team.
Requirements
- Strong Software Engineering background with a transition into the data/infrastructure space.
- 10+ years in software / data infrastructure with proven experience in inheriting an existing platform architecture.
- Deep hands-on experience with modern, code-first data architectures (event streaming, distributed processing, modern lakehouses, containerized orchestration).
- Focus on systems engineering over legacy systems.
- Understanding that schema and domain model ownership belongs to the engineering team.
- Excels at building internal tools and APIs that make data publishing/consumption frictionless.
- Able to review system design, weigh trade-offs between speed and technical debt, and stay close enough to the technology to earn the respect of senior engineers.
Nice To Haves
- Experience with real-time/event-driven healthcare or financial data streams (claims, clinical data, financial transactions).
- Background in HealthTech, FinTech, or another regulated industry handling sensitive data.
- Experience building data platforms specifically optimized for LLMs, product engineering, and production ML pipelines.
- Strong familiarity with HIPAA, PHI, zero trust security patterns in cloud environments.
Responsibilities
- Evolve & Modernize Data Infrastructure: Inherit and assess existing data systems, charting a pragmatic path to scale them using modern, code-driven software patterns and cloud-native tools.
- Build a Software-First Engineering Team: Hire, mentor, and lead a team of high-caliber software engineers who specialize in data pipelines, data processing, and database internals.
- Build the Platform, Not the Schema: Provide the infrastructure, streaming/batch frameworks, and APIs so product teams can own their domain models and schemas.
- Own the Data Lifecycle: Build robust, observable, high-performing capabilities for ingesting, transforming, storing, and exposing data for the IDR platform, AI/ML models, and internal services.
- Promote Software Engineering Best Practices: Employ rigorous software engineering practices across data pipelines including automated testing, IaC, version control, and observability.
- Security & Compliance Hardening: Implement programmatically enforced security, access controls, and privacy guardrails for sensitive data.
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
