Distinguished Data Systems Architect, Data Engineering

Distinguished Data Systems Architect, Data Engineering 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. 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. Overview of the Role 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. Key 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 Responsibilities 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 Qualifications 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 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. Compensation United States Salary Range: $219,100—$328,700 USD Base salary range does not include bonuses, equity, or benefits. Benefits 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 Equal Opportunity Statement GitLab is proud to be an equal opportunity workplace and 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 protected characteristics. #J-18808-Ljbffr