Distinguished Data Systems Architect, Data Engineering
GitLab
Distinguished Data Systems Architect, Data Engineering
Job Description
About this Role
Join GitLab as a Distinguished Data Systems Architect to spearhead the evolution of our strategic data platform.
Empower teams worldwide by architecting scalable, distributed solutions that redefine data management across deployments.
GitLab's mission is to enable everyone to contribute to and co-create the software powering our world.
This role accelerates human progress by uniting teams and breaking barriers in software development.
Embrace AI as a core productivity multiplier, integrating it into daily workflows for unmatched efficiency.
Drive innovation with products like Duo Enterprise and Duo Agent Platform at every SDLC stage.
Thrive in a high-performance culture fueled by values, continuous knowledge exchange, and collaboration.
Solve complex problems alongside industry leaders, reaching your full potential in an open-core environment.
Create unified blueprints aligning SaaS and self-managed platforms on cutting-edge standards.
Unlock new revenue streams through monetizable data services, governance, and AI-driven architectures.
Locations
- United States (Remote)
Salary
Salary details available upon request
300,000 - 500,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Pythonintermediate
- Dockerintermediate
- Airflowintermediate
- Trinointermediate
- Postgresintermediate
- Distributed query enginesintermediate
- Graph-based metadata systemsintermediate
- Kubernetesintermediate
- Argointermediate
- OpenTelemetryintermediate
Required Qualifications
- Experience architecting large-scale distributed data systems in complex, regulated domains (experience)
- Demonstrated leadership building multi-modal data services with monetization and governance focus (experience)
- Hands-on expertise with modern data stack technologies including Python, Docker, Airflow, Trino, Postgres (experience)
- Advanced knowledge bridging cloud and on-premises deployments with automation and self-service (experience)
- Deep understanding of data processing paradigms, schema management, and logical data modeling (experience)
- Experience with AI-driven architectures, model orchestration, and agentic patterns (experience)
- Strong architectural opinions on cost-aware, resilient solutions optimizing data lifecycle (experience)
- Passion for open source platforms, team mentorship, and collaborative values (experience)
- Design and implementation of Model Driven Architecture (MDA) frameworks (experience)
- Ability to transform ambiguous business challenges into strategic technical roadmaps (experience)
Preferred Qualifications
- Expertise in distributed query engines and graph-based metadata systems (experience)
- Familiarity with standards like OpenTelemetry, OpenMetadata, and OpenLineage (experience)
- Knowledge of event-driven architectures and Kubernetes orchestration (experience)
- Experience with data lineage, quality controls, and compliance practices (experience)
- Background in semantic modeling for internal analytics and external products (experience)
- Skills in balancing OLTP/OLAP performance, scalability, and cost-efficiency (experience)
- Proficiency in connector marketplaces for data integration (experience)
- Understanding of MCP (Model Context Protocol) and emerging technologies (experience)
- Proven track record in high-stakes architectural engagements (experience)
- History of embedding AI patterns into data infrastructure (experience)
Responsibilities
- Drive architectural vision for scalable data systems across deployments
- Establish enterprise data governance frameworks with lineage and quality controls
- Architect monetizable data services and APIs with semantic models
- Create cohesive architectural blueprint of GitLab's data ecosystem
- Design event-driven architectures and end-to-end data lifecycle systems
- Partner with leadership to embed AI-driven patterns into infrastructure
- Transform business challenges into strategic technical roadmaps
- Identify gaps against modern platforms and set design principles
- Ensure security, performance SLAs, and observability in data services
- Align senior leaders on common design tenets and platform standards
Benefits
- general: Competitive base salary with equity compensation
- general: Employee Stock Purchase Plan
- general: Flexible Paid Time Off
- general: Benefits to support health, finances, and well-being
- general: Team Member Resource Groups for inclusion
- general: Growth and Development Fund
- general: Parental leave
- general: Home office support and equipment
- general: Continuous learning opportunities
- general: High-performance culture with knowledge exchange
Tags & Categories
Distinguished Data Systems Architect, Data Engineering
GitLab
Distinguished Data Systems Architect, Data Engineering
Job Description
About this Role
Join GitLab as a Distinguished Data Systems Architect to spearhead the evolution of our strategic data platform.
Empower teams worldwide by architecting scalable, distributed solutions that redefine data management across deployments.
GitLab's mission is to enable everyone to contribute to and co-create the software powering our world.
This role accelerates human progress by uniting teams and breaking barriers in software development.
Embrace AI as a core productivity multiplier, integrating it into daily workflows for unmatched efficiency.
Drive innovation with products like Duo Enterprise and Duo Agent Platform at every SDLC stage.
Thrive in a high-performance culture fueled by values, continuous knowledge exchange, and collaboration.
Solve complex problems alongside industry leaders, reaching your full potential in an open-core environment.
Create unified blueprints aligning SaaS and self-managed platforms on cutting-edge standards.
Unlock new revenue streams through monetizable data services, governance, and AI-driven architectures.
Locations
- United States (Remote)
Salary
Salary details available upon request
300,000 - 500,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Pythonintermediate
- Dockerintermediate
- Airflowintermediate
- Trinointermediate
- Postgresintermediate
- Distributed query enginesintermediate
- Graph-based metadata systemsintermediate
- Kubernetesintermediate
- Argointermediate
- OpenTelemetryintermediate
Required Qualifications
- Experience architecting large-scale distributed data systems in complex, regulated domains (experience)
- Demonstrated leadership building multi-modal data services with monetization and governance focus (experience)
- Hands-on expertise with modern data stack technologies including Python, Docker, Airflow, Trino, Postgres (experience)
- Advanced knowledge bridging cloud and on-premises deployments with automation and self-service (experience)
- Deep understanding of data processing paradigms, schema management, and logical data modeling (experience)
- Experience with AI-driven architectures, model orchestration, and agentic patterns (experience)
- Strong architectural opinions on cost-aware, resilient solutions optimizing data lifecycle (experience)
- Passion for open source platforms, team mentorship, and collaborative values (experience)
- Design and implementation of Model Driven Architecture (MDA) frameworks (experience)
- Ability to transform ambiguous business challenges into strategic technical roadmaps (experience)
Preferred Qualifications
- Expertise in distributed query engines and graph-based metadata systems (experience)
- Familiarity with standards like OpenTelemetry, OpenMetadata, and OpenLineage (experience)
- Knowledge of event-driven architectures and Kubernetes orchestration (experience)
- Experience with data lineage, quality controls, and compliance practices (experience)
- Background in semantic modeling for internal analytics and external products (experience)
- Skills in balancing OLTP/OLAP performance, scalability, and cost-efficiency (experience)
- Proficiency in connector marketplaces for data integration (experience)
- Understanding of MCP (Model Context Protocol) and emerging technologies (experience)
- Proven track record in high-stakes architectural engagements (experience)
- History of embedding AI patterns into data infrastructure (experience)
Responsibilities
- Drive architectural vision for scalable data systems across deployments
- Establish enterprise data governance frameworks with lineage and quality controls
- Architect monetizable data services and APIs with semantic models
- Create cohesive architectural blueprint of GitLab's data ecosystem
- Design event-driven architectures and end-to-end data lifecycle systems
- Partner with leadership to embed AI-driven patterns into infrastructure
- Transform business challenges into strategic technical roadmaps
- Identify gaps against modern platforms and set design principles
- Ensure security, performance SLAs, and observability in data services
- Align senior leaders on common design tenets and platform standards
Benefits
- general: Competitive base salary with equity compensation
- general: Employee Stock Purchase Plan
- general: Flexible Paid Time Off
- general: Benefits to support health, finances, and well-being
- general: Team Member Resource Groups for inclusion
- general: Growth and Development Fund
- general: Parental leave
- general: Home office support and equipment
- general: Continuous learning opportunities
- general: High-performance culture with knowledge exchange
Tags & Categories