You'll own features end to end, from source integration to tested, monitored, documented data ready for use. You'll focus on keeping the platform reliable, secure, and cost-efficient as data volumes and AI usage grow, and making governed data ready for AI tools, agents, and Model Context Protocol (MCP)-based access. This is an AI-first role: you'll use AI coding agents every day while maintaining high standards for code review and testing. You'll report to the Director, Data Platform.
What you’ll do
Build, extend, and maintain extract, load, transform (ELT) pipelines from enterprise applications such as Salesforce, Zuora, Zendesk, and Marketo, internal systems, and the GitLab SaaS platform. Integrate data through application programming interfaces (APIs) and event sources such as Snowplow.
Manage and maintain the infrastructure behind the platform, including SaaS tools such as Snowflake, Fivetran, and Monte Carlo, and self-managed services such as Airflow and Kubernetes.
Write maintainable, well-tested, performant Python and Structured Query Language (SQL) code that meets our internal standards, and review GitLab team members' merge requests.
Own day-to-day platform operations: triage and resolve failed pipelines, infrastructure issues, and GitLab team member requests. Use monitoring, service-level agreements (SLAs), data contracts, query and warehouse tuning, and data quality checks to keep the platform reliable and cost-efficient.
Partner with Analytics Engineers, Data Analysts, Data Scientists, Data Governance, and business partners so data lands in the shape they need for downstream use.
Use AI coding agents such as Claude Code, OpenCode, GitLab Duo, or similar tools to speed up development, debugging, testing, and documentation without compromising review rigor.
Apply role-based access control (RBAC) and masking policies to make governed data available to AI tools and agents. Handle data subject to Sarbanes-Oxley (SOX) controls, material nonpublic information (MNPI), and personal data safely.
Ship medium-sized features independently in small, iterative merge requests, and document architecture and runbooks in the handbook.
What You'll Bring
Professional experience shipping production data pipelines in Python.
Deep, hands-on SQL skills and experience with a cloud data warehouse; Snowflake is preferred.
Hands-on experience with ELT or extract, transform, load (ETL) pipelines at scale, including incremental loads, schema changes, backfills, and API ingestion.
Experience with orchestration tools such as Airflow, familiarity with dbt, and solid data modeling fundamentals, including Kimball dimensional modeling.
Experience running and troubleshooting data infrastructure, with comfort using Git-based workflows, continuous integration and continuous delivery (CI/CD), and code review.
Hands-on experience using AI coding tools in your daily work, with an understanding of where they help and where they fall short.
Clear written communication, the ability to use GitLab, and comfort working asynchronously in a fully remote organization in line with GitLab's values.
Preferred, not required: experience with Snowflake; Docker, Kubernetes, Google Cloud Platform (GCP), or Terraform; SaaS application APIs such as Salesforce, Zuora, or Zendesk; data observability tooling; or Snowflake administration.
About the team
The Data Platform team within Enterprise Data is responsible for a scalable, reliable and secure data platform for data analytics at GitLab. That includes managing and maintaining the infrastructure we use, both SaaS and self-managed, and building and maintaining the data pipelines that bring data into it. We make data reliable, secure and ready for analytics, data science and AI tools. As more questions go straight to AI tools and agents, the platform underneath has to be more reliable, better governed and more cost-efficient than ever. We're fully remote and globally distributed, and work asynchronously through issues, merge requests and the handbook.
How GitLab Supports Full-Time Employees
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
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
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GitLab is proud to be an equal opportunity workplace and is 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 race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.
