> Markdown version of [/jobs/ext/2704785-pivotal-s-head-of-data-engineering](https://www.wearedevelopers.com/jobs/ext/2704785-pivotal-s-head-of-data-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Pivotal's Head of Data Engineering - **Company:** Pivotal Health, Inc. - **Location:** Brooklyn, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, Systems Engineering, Automation of Tests, Clinical Data Repository, Software Quality, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Data Systems, Distributed Computing Environment, Distributed Systems, Event-Driven Programming, Information Lifecycle Management, Machine Learning, Zero Trust Network Access, Software Construction, Software Engineering, SQL Databases, Data Streaming, Data Processing, Cloud Platform System, Large Language Models, Technical Debt, Backend, Machine Learning Operations, Software Version Control, Data Pipelines, Domain Model, Legacy Systems - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/head-of-data-engineering-pivotal-health-9610666 ## About the Role * You come from a strong Software Engineering background and moved into data/infrastructure space because you love building data-intensive distributed systems. * 10+ years in software / data infrastructure with proven experience in inheriting an existing platform architecture rather than needing a greenfield slate. * Deep hands-on experience with modern, code first data architectures (event streaming, distributed processing, modern lakehouses, containerized orchestration). You focus on systems engineering over legacy systems= * You understand schema and domain model ownership belongs to the engineering team. You excel 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., * 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 platform specifically optimized for LLMs, product engineering, and production ML pipelines * Strong familiarity with HIPAA, PHI, zero trust security patterns in cloud environments, If you're excited by solving complex problems and making a real-world impact, we'd love to hear from you., Candidates must be authorized to work in the United States without current or future employer sponsorship. ## Description We are hiring Pivotal's Head of Data Engineering, an engineering leader who will own the platform, architecture, and team powering our end-to-end data infrastructure. We view Data Engineering as a specialized discipline of Software Engineering, not a traditional analytics or database-administration function. We are looking for a systems-minded leader with strong software engineering fundamentals who treats data infrastructure with the same rigour as core backend services, emphasizing CI/CD, maintainability, scalability, and code quality over traditional GUI tools and SQL-only workflows. You will inherit an existing data foundation and lead its evolution into a modern, distributed, high-throughput platform. You will think holistically about data across its entire lifecycle: ingestion, processing, storage, and consumption interfaces. Rather than siloing data modeling within your team, you will build the platform and tools that enable the entire software engineering organization to own their schemas, publish clean data, and consume platform services seamlessly., * 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: Product, Engineering, AI, Business Intelligence teams are your primary customers. 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. ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [How to Domain Model – An example from manufacturing](https://www.wearedevelopers.com/videos/742-how-to-domain-model-an-example-from-manufacturing) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Full-stack role-based authorization in 45 minutes](https://www.wearedevelopers.com/videos/312-full-stack-role-based-authorization-in-45-minutes) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)