Engineering Manager, Data Foundations

We're looking for an experienced Engineering Manager to lead our Data Foundations team — the team responsible for data ingestion, data quality, and cost management across ServiceTitan's data platform. You'll stay hands-on and technically engaged, guiding architecture personally rather than delegating it, while building and leading a team of strong engineers across the US and India.

Lead and Mentor: Manage and grow a team of 5+ data engineers spanning multiple regions and time zones. Set clear expectations, provide regular feedback, and build a team culture rooted in ownership and psychological safety.

Hands-On Technical Leadership: Stay hands-on — review architecture and code, prototype solutions to hard problems, and personally guide the team's technical direction rather than delegating all design work.

Architecture, Data Quality & Cost: Drive architecture for data ingestion (Kafka, custom ETL Agent), Snowflake, and Airflow; own the strategy for data quality tooling and monitoring; and lead cost optimization efforts, balancing efficiency with reliability and long-term platform health.

Operations & Stakeholder Collaboration: Own the operational posture of the platform — monitoring, alerting, incident response, and on-call — while championing data governance best practices and partnering with product, architecture, and business stakeholders to deliver the roadmap.

Experience: 8+ years in data or software engineering, with 2+ years managing engineering teams of 5 or more.

Building & Leading Global Teams: Proven experience building and leading engineering teams across multiple regions and time zones, with strong async-first habits and comfort setting technical direction without relying on overlapping hours.

Technical Depth: Hands-on experience with Cloud Providers, Kubernetes, Kafka, Snowflake, Iceberg/Delta/Hudi, Airflow, and Python; a strong grasp of distributed systems trade-offs; and experience architecting data ingestion, quality, and cost-optimization solutions at scale.