Engineering Manager, Data Infrastructure

Scale AI is building the infrastructure and tooling to power the next generation of AI systems. The company works with leading AI teams to provide the data, compute, and evaluation capabilities needed to develop safer, more capable models at scale.

You'll join Scale AI as Engineering Manager for Data Infrastructure, leading the team that builds and operates the data warehousing and streaming systems everyone in the organization depends on. This is a high-visibility role where you'll own the complete data platform—from ingestion and event streaming through storage, orchestration, and reporting—while partnering with finance, product, engineering, and research teams to ensure data infrastructure directly enables business-critical decisions and company growth.

What you'll do

• Lead and grow the Data Warehouse & Streaming Infra team, mentoring engineers and building a culture of ownership, collaboration, and execution while managing rapid scaling

• Own the end-to-end data warehousing, streaming, and processing stack, including user experience, operations, reliability, security, governance, cost, and long-term strategic direction

• Architect and evolve data ingestion, event streaming, change data capture, storage, orchestration, compute, query, and reporting systems to keep pace with business growth

• Drive key platform decisions around the streaming backbone—such as managed versus self-operated Kafka—using clear models of throughput, cost, and operational burden

• Define data quality standards, freshness and delivery SLAs, and operational processes that guide the team through a high-change environment

• Hire senior data infrastructure engineers, sourcing and closing candidates who thrive in high-growth, high-trust settings

• Make sound infrastructure investment decisions with clear awareness of cost, capacity, reliability, and long-term maintainability tradeoffs

What you'll bring

• 3+ years of engineering management experience with a proven track record building and leading high-performing data infrastructure teams

• Deep hands-on expertise in both batch and streaming data infrastructure, including warehousing, pipelines, orchestration, event streaming, and change data capture, with solid understanding of distributed log fundamentals like partitioning, delivery guarantees, and backpressure

• A people-first leadership approach: you give direct feedback, grow engineers' careers, build trust across technical and non-technical partners, and maintain principled judgment as priorities shift

• Demonstrated ownership of systems with significant business or financial impact, shipping reliably at speed while improving scalability, security, and cost

• Sharp instincts for hiring and a track record building teams from small to large

Nice to have

• Experience with BigQuery, Snowflake, Iceberg, Spark, dbt, Airflow, Kafka, Pub/Sub, Flink, or Debezium, ideally at high scale

• Multi-cloud or multi-region data platform experience, including data-residency requirements

• Background in data infrastructure at AI or ML-intensive companies supporting model training, evaluation, or safety workflows

• Experience building and operating observability and monitoring for data systems at scale

What we offer

• Annual salary between 405,000 and 485,000 USD

• Visa sponsorship available; we retain an immigration lawyer and will make every reasonable effort to support successful sponsorships

• Hybrid arrangement with expectation of in-office presence at least 25% of the time in San Francisco or New York