Hinge Health

Hinge Health

Data Engineering Manager, Data & ML Platform

San Francisco-HQ

Sponsorship not specifiedDetected 49 days ago
PythonSQLDatabricksAWSCI/CDKafkaMachine LearningSparkdbtData EngineeringData ScienceA/B TestingIncident ResponseComplianceUnityHIPAACommunicationMentoring

About the role

  • As a Data Engineering Manager leading our Data & ML Platform team, you'll sit at the intersection of data engineering, real-time systems, and ML enablement, owning the platforms that make analytics, experimentation, and machine learning reliable at scale.
  • This is not a pure infrastructure or ML engineering role.
  • We're looking for a data platform leader with strong data modeling instincts, product awareness, and enough ML platform experience to bridge both worlds.

Responsibilities

  • 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.
  • 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.
  • 0→1 / 1→10 builder: You've stood up ML platform capabilities in a growth-stage or scaling company where systems were evolving and not fully mature - building patterns, not just operating pre-built infrastructure.
  • You hire and develop strong technical talent, give clear direction, and create an environment where engineers can do the best work of their careers.
  • 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.

Requirements

  • 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.
  • 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.

Nice to have

  • Experience standing up ML platform capabilities in a growth-stage or scaling environment, taking systems from 0→1 or 1→10, rather than only operating fully mature platforms at very large companies.
  • Demonstrated deep data platform fluency across data modeling, schema evolution, data contracts, pipeline orchestration, and data quality - with ML platform work as a natural extension of that foundation.
  • Background in regulated environments (e.g., HIPAA, SOC 2 or similar), with a strong orientation toward SLOs, observability, and incident management.
  • Experience with the Databricks ecosystem (Delta Lake, MLflow, Unity Catalog) or similar technologies.
  • Demonstrated AI-forward mindset, including experience incorporating AI tools into engineering workflows and mentoring teams on effective, safe AI-native practices.
  • The platform addresses a broad spectrum of MSK care - from acute injury, to chronic pain, to post-surgical rehabilitation - through personalized, evidence-based care.
  • The company is headquartered in San Francisco with additional offices in Montreal and Bangalore.
  • Learn more at www.hingehealth.com http://www.hingehealth.com.

Benefits

  • 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.
  • Hinge Health is an
  • Hinge Health is building the data and ML backbone that powers personalized MSK care for millions of members - from real-time product experiences to clinical insights and cost savings for our customers.

Equal opportunity

  • equal opportunity employer and prohibits discrimination and harassment of any kind.
  • If you feel you need assistance or an accommodation due to a disability, please let us know by reaching out to your recruiter.
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This listing is sourced directly from Hinge Health's careers page and normalized into a canonical job model.