At H1, we believe access to the best healthcare information is a basic human right. Our mission is to provide a platform that can optimally inform every doctor interaction globally. This promotes health equity and builds needed trust in healthcare systems. To accomplish this, our teams harness the power of data and AI-technology to unlock groundbreaking medical insights and convert those insights into action that result in optimal patient outcomes and accelerates an equitable and inclusive drug development lifecycle. Visit h1.com to learn more about us.

As part of H1’s hiring process, all candidates are required to participate in an in-person final interview. Depending on your location, this may require travel.

H1's Product Engineering organization is the engine behind the products that put our data in front of the people who need it most — health plans, digital health companies, life sciences organizations, and the clinical teams they serve. We build the client-facing products, APIs, integrations, and intelligent workflows that transform H1's rich underlying data into real decisions: which providers belong in a network directory, where clinical trials should run, and how healthcare organizations can operate with greater accuracy and trust. Product Engineering at H1 sits at the crossroads of complex data systems and enterprise software delivery, and our work directly drives revenue, client retention, and patient impact. We move fast, we own our products end-to-end, and we hold ourselves to a high bar — because in healthcare, the quality of what we build has consequences.

You will lead the engineering organization responsible for H1's quarterly data feed releases — HCP data, HCO (healthcare organization) data, and clinical trial data, as well as the buildout of DAM (Directory Accuracy Management), our configurable pipeline platform for ingesting customer-supplied provider directory data, running it through H1's accuracy and management processing, and delivering standardized outputs. The vision for DAM is moving from bespoke per-customer engineering to a fully productized, template-driven model where onboarding a new enterprise customer requires configuration, not custom code. You will drive that productization journey from where it is today through to completion.

You will:
- Own the full Data Streams engineering organization, leading engineering managers and senior ICs, setting technical vision, and building a culture grounded in accuracy, governance, and delivery reliability.
- Drive the DAM platform buildout across all phases: Foundation (canonical schemas, entity resolution, S3/SFTP delivery), Configurability (onboarding UI), Operations (alerting, observability), CSV flavors, POC mapping tool, and Enrichment, moving the team from bespoke per-customer engineering to a productized, configurable model.
- Own and enforce the Data Stream Governance framework, the quarterly release cadence, data dictionary contracts, track classifications (A/B/C), QA gates, and hotfix policy, ensuring every change shipped matches its documentation exactly and every release earns customer trust.
- Partner with Product, the Data Feeds Lead, Commercial, and Customer Success to align on schema decisions, new data sources, and the delivery roadmap and serve as the senior engineering voice in customer conversations about data contracts, delivery commitments, and onboarding timelines.
- Manage competing priorities across the engineering org, PM, CS, and sales, communicating tradeoffs clearly and making calls when schema changes, delivery timelines, or customer commitments conflict.
- Build and develop the engineering team, hiring, coaching, performance management, and developing engineering managers who can lead with the same discipline and accuracy-first instinct the platform requires.
- Drive triage and incident response for data delivery issues with urgency and transparency — owning root cause analysis, customer communication, and the QA gate improvements that prevent recurrence.
- Stay close enough to the technology to engage meaningfully in architecture and system design decisions — you won't be coding daily, but your engineers trust that when you weigh in, it's grounded in real understanding of how data moves through a governed delivery pipeline.

You've moved a team through productization before, from bespoke per-customer engineering to a configurable, template-driven model, and you know how hard that organizational and technical change is in practice. You've managed other engineering managers and know that developing a manager is a different skill from developing a senior IC. You are comfortable in commercial conversations with pharma and life sciences customers, and you have enough domain knowledge to be credible when the discussion turns to how their organizations consume and use external data feeds.

You thrive in environments where accuracy is the value proposition and the expectation is that you build the structure rather than wait for it. You are a clear communicator, a decisive decision-maker, and the kind of leader who makes their team feel the difference between delivering data and delivering data that can be trusted.