Data System Architect, Data Engineering & Monetization

August 5

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GitLab

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Artificial Intelligence • Enterprise • SaaS

GitLab is the most comprehensive AI-powered DevSecOps platform, offering tools for automated software delivery, security, and compliance throughout the software development lifecycle. It provides solutions across areas such as AI-assisted development, continuous integration/continuous deployment (CI/CD), source code management, and vulnerability management. GitLab aims to simplify and accelerate software delivery by uniting development, security, and operations on a unified platform. It is particularly recognized for its AI code assistants and has been named a leader in the Gartner Magic Quadrant™ for DevOps Platforms, making it a preferred choice for many enterprises.

1001 - 5000 employees

Founded 2014

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Secondary Market on 2020-11

📋 Description

• 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.

🎯 Requirements

• 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

🏖️ 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