The opportunity
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.
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.
What they're looking for
- 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.
