Engineering Manager Data Foundations

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.

• 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.

• 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.

In Data Foundations we enable customers to self-serve reporting with scalable architecture. Our vision is to build a comprehensive dashboards-as-a-service framework that uses AI and relies on scalable data infrastructure.

Data Insights Platform is one of our central initiatives and we play a key role in advancing self-service reporting across GitLab. This is the foundational layer every reporting and intelligence surface at GitLab depends on — from product dashboards to Software Engineering Intelligence to the GitLab Knowledge Graph.

In addition to Data Insights Platform the team’s scope will include classic search as part of the broader Data Foundations organization.This brings together foundational analytics and search capabilities that help customers generate insights from product data and find relevant information across GitLab.

We partner closely with product teams to turn DIP’s real-time insights Postgres-to-ClickHouse replication event routing and downstream exports into dashboards agent experiences and customer-facing reporting.

The scale expectations are real: we handle very large event volumes with current and projected usage in the hundreds of millions of events per day.

For more on how we work see:

• Platform Insights Group

• Data Insights Platform architecture blueprint

• Data Insights Platform Querying API

What We Do

GitLab is the Intelligent Orchestration Platform where software teams and their AI agents stay in flow to amplify their capacity for innovation. Together they automate repetitive tasks to plan build secure test deploy and maintain software. With GitLab software teams spend less time on coordination overhead and more time on the next big idea.What started in 2011 as an open source project to help one team of programmers collaborate is now the intelligent orchestration platform millions of people use to deliver software faster more efficiently while strengthening security and compliance.Since the beginning we've been firm believers in remote work open source DevSecOps and iteration. We get up and log on in the morning to work alongside the GitLab community to deliver new innovations every month that help teams and their AI agents ship great code faster.

Why Work With Us

GitLab is where careers accelerate innovation flourishes and every voice is valued. Co-create the future with us as we build technology that transforms how the world develops software.

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