Principal Data System Architect, Data Engineering & Monetization

GitLab; Canada; Remote; CAD 217,000 - 326,000; Full time

Job summary

A leading software company is seeking a Principal Data System Architect to drive the architectural vision for scalable, distributed data systems. The role involves defining product standards, building monetizable data services, and partnering with product teams. Candidates should have experience in architecting large-scale data systems and expertise with modern data stack technologies. This position offers remote work opportunities and a competitive salary range.

Qualifications

• Experience architecting large-scale distributed data systems in complex, regulated domains.
• Leadership building multi-modal data services with monetization focus.
• Hands-on expertise with technologies like Python, Docker, Airflow, and Trino.

Responsibilities

• Drive architectural vision for scalable data systems.
• Define enterprise data product standards and governance frameworks.
• Build governable data services and APIs.

Skills

Experience in architecting large-scale distributed data systems

Leadership building multi-modal data services

Expertise with modern data stack technologies

Knowledge of cloud and on-premises deployments

Understanding of data processing paradigms

Experience with AI-driven architectures

Architectural opinions on scalable solutions

Passion for open source platforms

Tools

Python

Docker

Airflow

Trino

Postgres

Job description

Overview

Principal Data System Architect, Data Engineering & Monetization — Remote options: Canada, EMEA, US.

GitLab is an open-core software company that develops a 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. We embrace AI as a core productivity multiplier and expect team members to incorporate AI into daily workflows to drive efficiency, innovation, and impact. We are committed to a high-performance culture driven by our values and continuous knowledge exchange.

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 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.

Salary and location: The base salary range for this role’s listed level is applicable to residents of listed locations. California/Colorado/Hawaii/New Jersey/New York/Washington, DC/Illinois/Minnesota pay range: $157,900 - $236,900 USD.

Country Hiring Guidelines: GitLab hires new team members in countries around the world. All roles are remote; some roles may have location-based eligibility requirements. Our Talent Acquisition team can answer questions about location after starting the recruiting process.

EEO Statement: GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. Our policies relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex, national origin, age, citizenship, marital status, disability, or other protected characteristics. See also GitLab’s EEO Policy.

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To apply, please submit your information through our standard application process. This job description reflects the responsibilities and requirements for this role and may be updated as needed.