Staff Data Engineer - Data & ML Platform

Ovii's Interpretation of the Role

The Staff Data Engineer will lead the architecture and reliability of Hinge Health's Data & ML Platform, delivering real‑time pipelines, analytical workloads, and ML services. This high‑ownership role works with a modern stack (Python, SQL, Flink, Kafka, AWS, etc.) and partners across engineering, data science, and product to ensure trustworthy, compliant data flows.

Role Snapshot

• Technical leader for data platform architecture
• Owner of data contracts, schema evolution, and governance
• Mentor for senior engineers and cross‑team collaborators
• Reliability champion for critical data pipelines
• Hands‑on builder of streaming and batch processing systems

Must-Have Requirements

• Python
• SQL
• Distributed data processing frameworks (PySpark, Flink, Spark)
• Kafka
• Cloud pipeline deployment (CI/CD, monitoring, incident response)
• Data modeling & warehouse design
• data engineering
• distributed processing
• cloud pipeline operations
• Bachelor’s Degree (or equivalent) in Computer Science, Engineering, or related technical field

Nice-to-Have Signals

• Data modeling and governance
• Streaming / event‑driven architecture
• Mentorship and engineering standards
• Product and business awareness
• Delta Lake
• dbt
• Airflow
• Aurora PostgreSQL
• AWS
• data modeling & governance
• streaming architecture
• mentoring engineers

Work Setup

• Location: San Francisco, USA
• Work mode: HYBRID
• Travel: occasional off‑site/on‑site events
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Travel
• Security clearance

What You'll Likely Work On

• Define and drive the architecture of the end‑to‑end data platform
• Design and implement streaming and batch pipelines on Flink, PySpark, and Kafka
• Establish data contracts, schema evolution policies, and governance standards
• Set reliability targets (SLAs/SLOs) and lead incident response for critical pipelines
• Build tooling and best‑practice guidance for upstream services to own their data
• Collaborate with product, data science, and SRE teams to align platform capabilities with business needs
• Mentor senior engineers through design reviews and technical coaching
• Balance performance, cost, and maintainability in platform decisions

Good Fit If You Have

• Enjoys solving ambiguous, cross‑team technical problems
• Thrives in a growth‑stage environment where foundational decisions matter
• Can translate product and business goals into data platform architecture