> Markdown version of [/jobs/ext/2737515-engineering-manager-data-platform](https://www.wearedevelopers.com/jobs/ext/2737515-engineering-manager-data-platform). 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). --- # Engineering Manager, Data Platform - **Company:** ADONIS INC. - **Location:** New York, United States - **Experience:** Experienced - **Salary:** $225,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Python (Programming Language), Open Database Connectivity, Operational Databases, Role-Based Access Control, Datadog, Fast Healthcare Interoperability Resources, Snowflake, Health Level Seven International, Build Process, Epic Clarity - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/engineering-manager-data-platform-adonis-9841869 ## About the Role * 8+ years in data or backend engineering, including 2+ years directly managing engineers with clear ownership of outcomes (delivery, performance management, hiring). * Genuine hands-on capability today, not historically. You can pass our coding screen and hold your own in a systems design discussion about warehouses, orchestration, and pipeline failure modes. * Direct experience operating production data platforms: warehouse architecture (Snowflake or similar), orchestration (Temporal, Airflow, or similar), and transformation frameworks (SQLMesh/dbt). * Evidence of building or scaling a team: hired well, grew people, and made at least one hard people call you can talk about honestly. * Stakeholder range: you manage up with judgment, push back with business framing, and keep relationships intact when you say no. * Startup metabolism: comfortable with lean teams, shifting priorities, and being close to the work. Nice to Have * Healthcare data experience: EHR integrations, claims (837/835), HL7/FHIR, PHI/HIPAA operating constraints. * Experience owning warehouse cost management, RBAC/governance, or vendor relationships (Snowflake, Fivetran). * Prior player-coach roles at Series A-C companies. ## Description You will lead a Data Platform team as a player-coach: owning the team's roadmap, delivery, and health while staying technically credible enough to review architecture, unblock hard problems, and contribute directly when the situation calls for it. This is a lean-team environment - you cannot operate as a pure management layer. In your first 30 days you should expect to be hands-on in the codebase and pipelines while you build context. The team operates on Snowflake, SQLMesh, Temporal, Python, and AWS, with Fivetran for ingestion and Datadog for observability. The mandate spans enterprise EHR extract infrastructure (Epic Clarity, Athena, ODBC-based sources), core entity modeling, hospital health-system readiness, and platform reliability, cost, and governance at growing scale. What You Will Do * Manage a team of 4-6 data platform engineers: performance, growth, coaching, and retention. * Own the team roadmap with product and the Head of Data. Turn ambiguous business needs into a sequenced, staffed plan and be accountable for delivery against it. * Set architecture direction with your senior ICs. Review designs, force the right trade-off conversations, and know when to overrule and when to defer. * Own hiring: sourcing, interviewing, closing, and raising the bar. Build the team the platform needs two quarters from now. * Run production: reliability, SLAs, on-call health, incident response, and warehouse cost as a first-class metric. * Operate across the org. Partner with DS/ML, forward-deployed engineering, and customer-facing teams; represent the platform to executives and, when needed, to enterprise customers. * Build process where it creates leverage and kill it where it does not: planning cadence, review practices, and quality bars appropriate to a startup, not a big company. * Drive an AI-native engineering culture. Integrate AI development tooling (Claude Code and similar) into how the team builds, reviews, and operates, and hold a bar for using it well. ## Related Videos - [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) - [Debugging in the Dark](https://www.wearedevelopers.com/videos/1658-debugging-in-the-dark) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Software Engineering Social Connection: Yubo’s lean approach to scaling an 80M-user infrastructure](https://www.wearedevelopers.com/videos/1583-software-engineering-social-connection-yubo-s-lean-approach-to-scaling-an-80m-user-infrastructure) ## 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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [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)