Data Engineering Manager, Data & ML Platform

Ovii's Interpretation of the Role

The Data Engineering Manager will lead the Data & ML Platform team, shaping streaming‑first, ML‑ready architecture and delivering reliable data pipelines and ML services. This role blends hands‑on data engineering, product awareness, and people management to enable Data Science and product teams at scale.

Role Snapshot

• Lead data & ML platform team
• Own streaming‑first data architecture
• Partner with Data Science and Product
• Drive reliability, observability, and SLOs
• Build feature store and model serving layer
• Establish data contracts and schema governance
• Mentor and grow engineering talent
• Implement CI/CD and testing tooling

Must-Have Requirements

• Data engineering
• ML platform development
• Streaming technologies (Kafka, Flink, Spark)
• Python
• SQL
• dbt
• Databricks
• AWS
• hands‑on data engineering
• engineering team management
• Bachelor's degree in Computer Science, Engineering, or related field

Nice-to-Have Signals

• Deep data platform fluency (modeling, schema evolution, contracts)
• Experience with regulated environments (HIPAA, SOC 2)
• AI‑assisted development workflows
• Experience with Databricks ecosystem (Delta Lake, MLflow, Unity Catalog)
• building ML platforms in growth‑stage environments
• regulated environment experience

Work Setup

• Location: San Francisco, USA
• Work mode: HYBRID
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Deeply understand existing batch and streaming pipelines, data models, and quality posture
• Partner with Data Science, Product, and engineering teams to prioritize ML and product use cases
• Stabilize core pipelines, define SLOs, and build observability baselines
• Evolve the platform toward a streaming‑first, ML‑ready architecture
• Design and launch the first iteration of a feature store and model serving patterns
• Drive schema governance and data contracts across upstream services
• Introduce tooling, templates, CI/CD, and testing to boost developer productivity
• Own the end‑to‑end platform roadmap, architecture, and operational excellence

Good Fit If You Have

• Built ML platform capabilities in a growth‑stage or scaling company
• Experience working in regulated environments (HIPAA, SOC 2)
• AI‑forward mindset with experience integrating AI tools into engineering workflows
• Strong product curiosity and ability to translate Data Science needs into engineering execution