Job Title: Data Platform Manager
Location: New York, NY (3 Days onsite)
Duration: Full-time
Job 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.
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.
What You Will Bring
- 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.
