Data Engineering Manager, Data & ML Platform

Hinge Health

Data 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

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Hard Skills

data engineeringproduction data pipelinesdata platformsdata infrastructureML platform capabilitiesfeature pipelinesfeature storesmodel servingbatch systemsstreaming systems

Soft Skills

team managementmentoringownershipexecution habitsdeveloper experiencepartnershipoperational rigorclarity of ownershipcommunicationcollaboration

Tools & Technologies

KafkaFlinkSparkPythonSQLdbtDatabricksAWSCI/CDobservability

Certifications & Qualifications

HIPAASOC 2

Industry Keywords

data qualityschema governancedata contractsreliabilityscalabilitydata ecosystemoperational excellenceanalyticsdata modelschange management

Tech Stack

Tools & technologies

AWSKafkaPythonSparkSQL

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.