GitLab is an open-core software company that develops the most comprehensive AI-powered DevSecOps Platform, used by more than 100,000 organizations. Our mission is to enable everyone to contribute to and co-create the software that powers our world. When everyone can contribute, consumers become contributors, significantly accelerating human progress. Our platform unites teams and organizations, breaking down barriers and redefining what's possible in software development. Thanks to products like Duo Enterprise and Duo Agent Platform, customers get AI benefits at every stage of the SDLC.
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. Co-create the future with us as we build technology that transforms how the world develops software.
An overview of this role
Join GitLab as Data System Architect to drive our strategic data platform evolution. You'll architect scalable, distributed solutions that transform how we manage and leverage data across our SaaS and self-managed deployments, supporting enterprise-scale growth and innovation.
What You’ll Do
- Drive architectural vision for scalable, distributed data systems across SaaS and self-managed deployments, designing database stack solutions that optimize OLTP/OLAP performance and scalability requirements
- Define enterprise data product standards and governance frameworks including data lineage, SDLC, versioning, and compliance practices for regulated environments
- Build governed, monetizable data services and APIs that support both internal operations/analytics and external SaaS product offerings with semantic structure
- Partner with product and engineering teams to embed modern agentic and AI-driven patterns into data infrastructure and customer-facing solutions
- Architect event-driven systems and cross-stack orchestration supporting hybrid transformations through tools like Argo, Airflow, and Kubernetes with unified metadata-rich telemetry
- Design end-to-end data lifecycle architecture covering integration, pipelines, transformation workflows, and consolidated metadata systems across multiple platforms
- Establish CI/CD best practices for data systems ensuring reliable deployment, monitoring, and maintenance across diverse deployment models
- Transform ambiguity into strategic roadmaps and lead complex technical engagements where data architecture creates competitive differentiation
What You’ll Bring
- Experience architecting large-scale distributed data systems in complex, regulated domains with unified platforms integrating cloud-native compute, orchestration, and semantic modeling
- Demonstrated leadership building multi-modal data services with strong developer experience principles, focusing on monetization, governance, and data product lifecycle management
- Hands-on expertise with modern data stack technologies including Python, Docker, Airflow, Trino, Postgres, distributed query engines, and graph-based metadata systems, integrating them into the GitLab ecosystem comprised of Ruby on Rails and Go services.
- Advanced knowledge bridging cloud and on-premises deployments with automation, developer self-service focus, and data integration through connector marketplaces
- Deep understanding of data processing paradigms and standards including synchronous vs. asynchronous processing, schema management, logical data modeling, and formats like OpenTelemetry, OpenMetadata, and OpenLineage
- Experience with AI-driven architectures and emerging technologies including model orchestration, agentic patterns, and standards like MCP (Model Context Protocol)
- Strong architectural opinions on cost-aware, resilient solutions that optimize entire data lifecycle decisions with focus on scalability and performance trade-offs
- Passion for open source platforms, team mentorship, and collaborative values with ability to build scalable solutions that align with organizational culture and technical excellence
About the team
Data Engineering and Monetization is a newly formed function within the Engineering Org with a mission to build a comprehensive foundation of data platforms with responsible data architecture that scales.
The base salary range for this role’s listed level is currently for residents of listed locations only. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, and alignment with market data. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
