Engineering Manager, Data Foundations

As Engineering Manager, Data Foundations you will manage and grow a high-performing team working on a core data platform that ingests, processes, persists, and queries data streams generated across GitLab. This role goes well beyond people management and into the architecture of high-throughput, multi-component data systems: ingestion, buffering, enrichment, replication, storage, querying, backpressure handling, and tenant isolation across GitLab.com, Dedicated, Self-Managed, and Cells-based deployments. The platform is built around stateless ingesters, Siphon CDC replication, NATS/JetStream buffering, enrichment pipelines, ClickHouse-backed storage, and a Query API that interfaces with the GitLab Rails monolith. The role also takes on classic search scope as that team joins the Data Foundations organization.

Responsibilities

• Hire, manage, and enable a high-performing Data Insights Platform engineering team.
• Partner with product managers, designers, and peer engineering managers to define and deliver the roadmap for the Data Insights Platform, Siphon, Query API integrations, classic search initiatives, and self-service reporting foundations.
• Own delivery for the team, including planning, prioritization, execution, and operational follow-through with clear accountability for roadmap milestones.
• Guide the technical design of distributed data-path components and shape architecture choices on sharding, partitioning, scaling, failure recovery, and tenant isolation.
• Help the team design safe, scalable integrations with the GitLab monolith, including gRPC/Protobuf-based query paths and clear ownership boundaries.
• Drive a high bar for security, privacy, and governance in how platform data is handled, including authentication, authorization, and encryption.
• Improve operational maturity across observability, capacity planning, performance monitoring, and runbooks for managed environments.

Qualifications

• Experience managing platform, infrastructure, or data systems teams at scale, with a track record of building high-performing teams.
• Deep distributed systems expertise: service boundaries, asynchronous pipelines, backpressure, fault tolerance, and operating multi-component systems in production.
• Strong technical background in backend and platform engineering, able to guide architecture for high-throughput event pipelines.
• Experience with change data capture, event streaming or messaging systems, OLAP data stores, query-serving layers, and service-to-service APIs.
• Ability to hire, develop, and coach team members while still contributing technical guidance on complex architecture.