Data Engineering Manager, Data & ML Platform

The Opportunity

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. As a Data Engineering Manager leading our Data & ML Platform team youll 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. Youll guide our evolution toward a streaming-first ML-ready architecture shaping how data flows consistently across systems and how product and Data Science teams build on top of it all in service of reducing pain and improving movement for people around the world.

This is not a pure infrastructure or ML engineering role. Were looking for a data platform leader with strong data modeling instincts product awareness and enough ML platform experience to bridge both worlds. Our data platform is maturing and our ML platform capabilities are still early youll make foundational architecture decisions partner with Data Science to operationalize models and lead both the team and the technical direction as a tech lead manager.

Hinge Health operates a hybrid model in San Francisco. We believe that remote work and in-person work have their own advantages and disadvantages and we want to leverage the best of both worlds. Employees in hybrid roles are required to be in the office 3 days per week for the full 8 hours of a typical business day. The San Francisco office has a dog-friendly workplace program.

What Youll Accomplish

In your first 3 months you will:

• 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.

In your first 6 months you will:

• 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.

In your first 12 months you will:

• 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 2oriented environment in close partnership with Security and Compliance.

Who You Are

• Data platform-first ML-fluent: Your roots are in data engineering and data platforms and youre equally comfortable thinking about data modeling schema evolution data contracts orchestration and data quality as you are about feature stores model serving and ML workflows.

• Product-minded systems thinker: You dont build infrastructure in a vacuum; you seek to understand the analytics product and ML use cases youre enabling and design platforms that are intuitive safe and flexible for your customers.

• 01 / 110 builder: Youve 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.

• Operationally rigorous: You treat reliability observability incident response and guardrails in regulated environments as first-class product features of the platform.

• AI-forward engineering leader: Youre excited about AI-assisted development workflows and can coach your team on using AI tools to move faster while maintaining high engineering standards.

• People-first manager: You hire and develop strong technical talent give clear direction and create an environment where engineers can do the best work of their careers.

Basic Qualifications

• 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.

Preferred Qualifications

• Experience standing up ML platform capabilities in a growth-stage or scaling environment taking systems from 01 or 110 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.

• Strong product and business curiosity: you quickly learn the domain understand how analytics and ML drive outcomes and translate Data Science needs into clear engineering execution.

• 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.

About Hinge Health

At Hinge Health were using technology to scale and automate the delivery of healthcare starting with musculoskeletal (MSK) conditions which affect over 1.7 billion people worldwide. With an AI-powered human-centered care model Hinge Health leverages cutting-edge technology to improve outcomes experiences and costs to help people move beyond their pain. The platform addresses a broad spectrum of MSK care from acute injury to chronic pain to post-surgical rehabilitation through personalized evidence-based care. As the preferred partner to 50 health plans PBMs and other ecosystem partners Hinge Health is available to over 20 million people across more than 2550 employers. The company is headquartered in San Francisco with additional offices in Montreal and Bangalore. Learn more at .

What Youll Love About Us

• 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 isnt 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.

Culture & Equal Opportunity

Hinge Health is an equal opportunity employer and prohibits discrimination and harassment of any kind. We make employment decisions without regard to race color religion sex sexual orientation gender identity national origin age veteran status disability status pregnancy or any other basis protected by federal state or local law. We also consider qualified applicants regardless of criminal histories consistent with legal requirements. We provide reasonable accommodations for candidates with disabilities. If you feel you need assistance or an accommodation due to a disability please let us know by reaching out to your recruiter. By submitting your application you are acknowledging we are using your personal data as outlined in the personnel and candidate privacy policy.

Beware of Phishing Attempts: Weve noticed an increase in phishing where fraudsters impersonate employees and send fake job offers to steal sensitive information. Well never ask for financial details during the hiring process and only use @ emails. If you receive a suspicious offer stop communication and report it to the US FBI Internet Crime Complaint Center. To verify an email from our recruiting team forward it to .

Required Experience:

Manager