Engineering Manager, Data Foundations

Details

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100 trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.

Overview

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. The role requires leveraging AI to drive productivity gains across the platform and deep distributed systems knowledge. You will work on architecture and production operations across ingestion, buffering, enrichment, replication, storage, querying, backpressure handling, isolation, and multi-deployment operations (GitLab.com, Dedicated, Self-Managed, and Cells).

The team’s scope includes the Data Insights Platform (DIP) and classic search capabilities. You’ll help lead architecture and execution across analytics and search, balancing platform depth with customer-facing impact.

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 Data Insights Platform (DIP) and related initiatives (including Siphon, Query API integrations, classic search, and self-service reporting foundations).
• Own delivery for your team: planning, prioritization, execution, and operational follow-through across architecture, platform improvements, and production readiness.
• Guide technical design of distributed data-path components (ingestion, buffering, enrichment, exporting, querying) and shape architecture choices on sharding, partitioning, scaling, failure recovery, and tenant isolation across SaaS, Dedicated, self-managed, and Cells deployments.
• Help 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 GraphQL or REST endpoints.
• Drive a high bar for security, privacy, and governance in how platform data is handled (authentication, authorization, encryption, privacy classifications).
• Improve operational maturity: observability, metrics, logging, readiness, capacity planning, performance monitoring, and runbooks for managed environments.
• Collaborate asynchronously across teams to land customer-facing reporting capabilities on top of the platform.
• Lead platform design with a focus on modular architecture and extensibility for AI-driven integrations.

Requirements

• 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: service boundaries, asynchronous pipelines, backpressure, fault tolerance, horizontal scalability, and operating multi-component systems in production.
• Strong technical background in backend and platform engineering; ability to guide architecture for high-throughput event pipelines and data systems.
• Experience with relevant technologies and patterns such as change data capture, event streaming/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 architecture and delivery tradeoffs.
• Strong cross-functional collaboration skills and experience building or operating systems across multiple deployment models (GitLab.com, Dedicated, self-managed, cell-based).
• Strong written communication skills and effectiveness in an all-remote, asynchronous environment.
• Familiarity with search, indexing, and query-serving systems is a strong plus.
• Passion for reliability, customer outcomes, and engineering and operational excellence.

About the team

In Data Foundations we enable customers to self-serve reporting with scalable architecture. Our vision is to build a dashboards-as-a-service framework that uses AI and relies on scalable data infrastructure. Data Insights Platform is a central initiative, enabling self-service reporting across GitLab and providing the foundational layer for product dashboards, Software Engineering Intelligence, and the GitLab Knowledge Graph. The team handles very large event volumes (current and projected usage in the hundreds of millions of events per day).

Salary

United States Salary Range: $152,800 - $259,200 USD

This base salary range is currently for residents of the United States only and does not include bonuses, equity, or benefits.

How GitLab Supports Full-Time Employees

• Benefits to support health, finances, and well-being
• Flexible Paid Time Off
• Team Member Resource Groups
• Equity Compensation & Employee Stock Purchase Plan
• Growth and Development Fund
• Parental Leave

Hiring & Privacy

GitLab hires new team members in countries around the world. All roles are remote, but some roles may carry location-based eligibility requirements; Talent Acquisition can help answer location questions after starting the recruiting process. Please review the Recruitment Privacy Policy for details on candidate privacy.