Engineering Manager, Data Foundations

Details

GitLab is seeking an Engineering Manager to lead and grow a high-performing engineering team within the Data Foundations group. The team builds a core data platform that ingests, processes, persists, and queries data streams generated across GitLab. The role combines people management with hands-on technical leadership across high-throughput, distributed data systems and AI-enabled productivity initiatives.

The platform supports GitLab.com, Dedicated, Self-Managed, and Cells-based deployments and includes stateless ingesters, Siphon change data capture replication, NATS/JetStream buffering, enrichment pipelines, ClickHouse-backed storage, and a Query API integrated with the GitLab Rails monolith. The role also includes classic search, indexing, query-serving systems, and self-service reporting foundations.

Responsibilities

• Hire, manage, coach, and develop a high-performing Data Insights Platform engineering team.
• Partner with product managers, product designers, and engineering managers to define and deliver the Data Insights Platform roadmap and related initiatives, including Siphon, Query API integrations, classic search, and self-service reporting.
• Own planning, prioritization, execution, production readiness, and operational follow-through for the team.
• Guide the technical design of distributed data-path components, including ingestion, buffering, enrichment, exporting, and querying.
• Shape architecture decisions involving sharding, partitioning, component-specific scaling, failure recovery, and tenant isolation across SaaS, Dedicated, Self-Managed, and Cells deployments.
• Guide safe and scalable integrations with the GitLab monolith, including gRPC and Protobuf-based query paths and ownership boundaries between platform and product teams using GraphQL or REST endpoints.
• Drive security, privacy, and governance practices covering authentication, authorization, encryption, and data with different privacy classifications.
• Improve observability, metrics, logging, readiness, capacity planning, performance monitoring, runbooks, availability, throughput, latency, and time to recovery.
• Collaborate asynchronously across teams and functions to deliver customer-facing reporting capabilities.
• Lead modular platform architecture that is extensible and ready for AI-driven integrations.

Requirements

• Experience managing platform, infrastructure, or data systems teams at scale and building high-performing teams.
• Deep distributed systems expertise, including service boundaries, asynchronous pipelines, backpressure, fault tolerance, horizontal scalability, and production operations.
• Strong backend and platform engineering background, with the ability to guide architecture for high-throughput event pipelines and data systems.
• 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 engineers while contributing technical guidance on complex architecture and delivery tradeoffs.
• Strong cross-functional collaboration skills when platform and feature-team ownership is shared.
• Experience operating systems across multiple deployment models, including SaaS, 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.
• Passion for reliability, customer outcomes, engineering excellence, and operational excellence.

About the Team

Data Foundations enables scalable, self-service reporting architecture and is building a dashboards-as-a-service framework that uses AI and scalable data infrastructure. Data Insights Platform supports reporting and intelligence surfaces including product dashboards, Software Engineering Intelligence, and the GitLab Knowledge Graph. The platform handles very large event volumes, with current and projected usage in the hundreds of millions of events per day.

Compensation

The United States base salary range is $152,800–$259,200 USD per year. The range excludes bonuses, equity, and benefits. Grade level and salary are determined based on factors including experience, skills, education, equity, market data, and geographic location.

Benefits

• Health, financial, and well-being benefits
• Flexible paid time off
• Team Member Resource Groups
• Equity Compensation and Employee Stock Purchase Plan
• Growth and Development Fund
• Parental Leave