Distinguished Data Systems Architect, Data Engineering

Remote

Git Lab is an open‑core software company that develops the most comprehensive AI‑powered Dev Sec Ops  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. Git Lab 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 Git Lab 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 Git Lab’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 Git Lab'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 Open…