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Data Engineering Manager, Data & ML Platform
Hinge HealthData Engineering Manager leading Data & ML Platform team at Hinge Health. Responsible for shaping analytics and machine learning reliability across systems.
Posted 6/3/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $220,000 - $330,000 per yearWebsite
Tech Stack
Tools & technologiesAWSKafkaPythonSparkSQL
About the role
Key responsibilities & impact- Deeply understand our current data and ML platform: batch and streaming pipelines, data models, orchestration, and data quality posture across analytics and production systems.
- Build strong partnerships with Data Science, Product, and other engineering teams; align on top ML and product use cases the platform must unlock.
- Take ownership of a subset of core pipelines and services, stabilizing reliability and on-call practices while establishing clear SLOs and observability baselines for the team.
- Lead the evolution of our data platform toward a streaming-first, ML-ready architecture, improving data freshness, consistency, and discoverability across domains.
- Design and deliver the first iteration of our ML platform layer — feature pipelines, feature store, and model serving patterns — enabling Data Science teams to self-serve within shared governance and operational standards.
- Drive schema governance and data contracts with upstream service teams to reduce fragmentation, standardize core data models, and improve reliability for downstream analytics and ML consumers.
- Invest in developer productivity: introduce tooling, templates, CI/CD, and testing practices that make it significantly easier for product and ML teams to build on the platform.
- Own and evolve the end-to-end data & ML platform strategy, including roadmap, architecture, and operational excellence across streaming, batch, and ML workloads.
- Partner with Data Science to operationalize models in production — from feature pipelines to serving, monitoring, and retraining — and embed these workflows into our broader data ecosystem.
- Build, mentor, and retain a high-performing data engineering team, creating clarity of ownership, strong execution habits, and a culture that raises the bar on reliability, scalability, and developer experience.
- Institutionalize operational rigor (SLOs, incident management, observability, change management) appropriate for a HIPAA/SOC 2–oriented environment, in close partnership with Security and Compliance.
Requirements
What you’ll need- 5+ years of hands-on data engineering experience, building and operating production data pipelines, data platforms, and data infrastructure at scale.
- 2+ years of experience managing engineering teams, with a track record of hiring, developing, and retaining technical talent.
- 2+ years of experience building ML platform capabilities (e.g., feature pipelines, feature stores, model serving, or ML workflow infrastructure) in a production environment.
- Experience building data platforms across batch and streaming systems, including technologies such as Kafka, Flink, Spark, or equivalent.
- Proficiency with a modern data stack such as Python, SQL, Spark, dbt, Databricks, and AWS (or comparable tools), and comfort evaluating new technologies in this space.
Benefits
Comp & perks- Inclusive healthcare and benefits: On top of comprehensive medical, dental, and vision coverage, we offer employees and their family members help with gender-affirming care, tools for family and fertility planning, and travel reimbursements if healthcare isn’t available where you live.
- Planning for the future: Start saving for the future with our traditional or Roth 401(k) retirement plan options which include a 2% company match.
- Modern life stipends: Manage your own learning and development with stipends that support modern life and growth.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringproduction data pipelinesdata platformsdata infrastructureML platform capabilitiesfeature pipelinesfeature storesmodel servingbatch systemsstreaming systems
Soft Skills
team managementmentoringownershipexecution habitsdeveloper experiencepartnershipoperational rigorclarity of ownershipcommunicationcollaboration
Certifications
HIPAASOC 2