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.
Join GitLab as a Distinguished Data Systems 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.
Some examples of our projects:
- Creating a unified architectural blueprint for GitLab’s data ecosystem that aligns SaaS and self-managed platforms on shared patterns and standards
- Designing monetizable data services and APIs with strong governance and observability to support new product offerings and revenue streams
- Drive architectural vision for scalable, distributed data systems across SaaS and self-managed deployments, designing database solutions that balance OLTP/OLAP performance, scalability, and cost-efficiency
- Establish enterprise data governance frameworks including lineage, quality controls, versioning, and compliance practices that meet regulatory requirements across global markets
- Architect monetizable data services and APIs with semantic models serving internal analytics and external product offerings, enabling new revenue streams while maintaining security and performance SLAs
- Create a cohesive architectural blueprint of GitLab's data ecosystem, identifying gaps against modern platforms and establishing opinionated design principles grounded in proven cloud-native patterns
- Design event-driven architectures and end-to-end data lifecycle systems spanning ingestion, orchestration (Argo, Airflow, Kubernetes), transformation workflows, and unified metadata management with comprehensive observability
- Partner with product and engineering leadership to embed AI-driven patterns into data infrastructure and align senior engineering leaders on common design tenets and platform standards
- Transform ambiguous business challenges into strategic technical roadmaps, leading high-stakes architectural engagements where data platforms create measurable competitive differentiation
- 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
- 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
- Design and implement Model Driven Architecture (MDA) framework to establish clear separation between logical/conceptual data models and platform-specific physical implementations, enabling agility and reducing technical debt across enterprise data systems
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 the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. 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, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. 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.
- Benefits to support your 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
- Home office support
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.
