Engineering Manager, Data Foundations

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 recovery.
• Collaborate asynchronously across teams and functions to help GitLab land customer-facing reporting capabilities on top of a strong, scalable data foundation.
• Lead the design and evolution of the platform with a focus on modular architecture, ensuring systems are extensible and ready for AI-driven integrations.

What you’ll bring

• Experience managing platform, infrastructure, or data systems teams at scale, with a track record of building high-performing, values-aligned teams.
• Deep distributed systems expertise, including strong judgment on service boundaries, asynchronous pipelines, backpressure, fault tolerance, horizontal scalability, and operating multi-component systems in production.
• Strong technical background in backend and platform engineering, with the ability to guide architecture for high-throughput event pipelines and data systems.
• Experience with technologies and patterns relevant to this space, such as 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 and delivery tradeoffs.
• Strong cross-functional collaboration skills, especially when ownership is split between platform teams and feature teams consuming common infrastructure or APIs.
• Experience building or operating systems across multiple deployment models, with sound judgment about the tradeoffs between GitLab.com, Dedicated, self-managed, and cell-based environments.
• Strong written communication skills and the ability to work effectively in an all-remote, asynchronous environment.
• Familiarity with search, indexing, and query-serving systems is a strong plus.
• A deep passion for reliability, customer outcomes, and engineering and operational excellence, with a proven track record of instilling these values in high-performing teams.