Engineering Manager, Data Foundations

An overview of this role As Engineering Manager at GitLab, you’ll manage and grow a high-performing engineering team within the Data Foundations group, working on a core data platform that ingests, processes, persists, and queries data streams generated across GitLab. We are looking for a leader who can leverage AI to drive non-linear productivity gains across the platform, accelerating our ability to deliver value to our customers. We’re looking for someone with deep distributed systems knowledge. You’ll need to be comfortable going well beyond people management and into the architecture of high-throughput, multi-component data systems: ingestion, buffering, enrichment, replication, storage, querying, backpressure handling, isolation, and production operations across multiple deployment models. You’ll partner closely with Product, Design, Infrastructure, Data, and other Engineering teams to evolve a platform that lives inside the product, keeps external services to a minimum, and runs across GitLab.com, Dedicated, Self-Managed, and Cells-based deployments. In addition to Data Insights Platform, this role will take on classic search scope as the team joins the Data Foundations organization. You’ll help lead architecture and execution across both GitLab’s analytics platform and classic search capabilities, balancing platform depth with customer-facing impact. You’ll help lead architecture and execution across both GitLab’s analytics platform and classic search capabilities, balancing platform depth with customer-facing impact. In this role, you’ll balance technical guidance with people management. You’ll hire, coach, and develop engineers while also helping drive architecture and execution across a platform 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. In Data Foundations, we build the engineering systems that make platform data reliable, scalable, and available to product teams across GitLab, and you’ll help guide that work. What you’ll do - Hire, manage, and enable a high-performing Data Insights Platform engineering team, creating an environment where team members can do their best work and deliver strong results. - Partner closely with product managers, product designers, and peer engineering managers to define and deliver the roadmap for Data Insights Platform (DIP) and related Platform Insights initiatives such as Siphon , Query API integrations, classic search initiatives, and self-service reporting foundations. - Own delivery for your team, including planning, prioritization, execution, and operational follow-through across architecture work, platform improvements, and production readiness, with clear accountability for roadmap milestones and delivery outcomes. - Guide the technical design of distributed data-path components, including ingestion, buffering, enrichment, exporting, and querying, and shape architecture choices on sharding, partitioning, component-specific scaling, failure recovery, and tenant isolation across SaaS, Dedicated, self-managed, and Cells deployments, with a strong focus on reliability, throughput, operability, and maintainability. - Help the team design safe and scalable integrations with the GitLab monolith, including gRPC/Protobuf-based query paths and clear ownership boundaries between DIP and product teams building user-facing GraphQL or REST endpoints. - Drive a high bar for security, privacy, and governance in how platform data is handled, including authentication, authorization, encryption, and safe handling of data with different privacy classifications. - Improve operational maturity across the platform, including observability, metrics, logging, readiness, capacity planning, performance monitoring, and clear runbooks for managed environments, with a focus on improving availability, throughput, latency, and time to recove