Hinge Health - Data Engineering Manager, Data & ML Platform

• Data platform-first, ML-fluent: Your roots are in data engineering and data platforms, and you’re 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. • Data platform-first, ML-fluent: • Product-minded systems thinker: You don’t build infrastructure in a vacuum; you seek to understand the analytics, product, and ML use cases you’re enabling and design platforms that are intuitive, safe, and flexible for your customers. • Product-minded systems thinker: • 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. • 0→1 / 1→10 builder: • Operationally rigorous: You treat reliability, observability, incident response, and guardrails in regulated environments as first-class product features of the platform. • Operationally rigorous: • AI-forward engineering leader: You’re excited about AI-assisted development workflows and can coach your team on using AI tools to move faster while maintaining high engineering standards. • AI-forward engineering leader: • 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. • People-first manager: • 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. • 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. • 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. • At Hinge Health, we’re 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 2,550 employers. The company is headquartered in San Francisco with additional offices in Montreal and Bangalore. Learn more at www.hingehealth.com.