Intermediate Data Engineer

About the role

As a Data Engineer at GitLab you will build, run and maintain the pipelines and infrastructure that bring data from enterprise applications, internal systems and GitLab's SaaS platform into the data platform, powering company reporting, data science and AI self-service. You will own features end to end, keep the platform reliable, secure and cost-efficient, and make governed data ready for AI tools, agents and MCP-based access. This is an AI-first role using AI coding agents daily. You report to the Director, Data Platform.

What you will do

• Build and maintain ELT pipelines from applications such as Salesforce, Zuora, Zendesk and Marketo, internal systems and the GitLab SaaS platform; integrate APIs and event sources such as Snowplow.
• Manage platform infrastructure including Snowflake, Fivetran and Monte Carlo, and self-managed services such as Airflow and Kubernetes.
• Write maintainable, well-tested Python and SQL; review merge requests.
• Run day-to-day operations: triage failed pipelines and infrastructure issues; use monitoring, SLAs, data contracts, query tuning and data quality checks.
• Partner with Analytics Engineers, Data Analysts, Data Scientists and Data Governance.
• Apply RBAC and masking policies; handle SOX, MNPI and personal data safely.

What you will bring

• Production data pipelines in Python; deep SQL and a cloud data warehouse (Snowflake preferred).
• ELT/ETL at scale: incremental loads, schema changes, backfills, API ingestion.
• Orchestration tools such as Airflow, familiarity with dbt, and data modelling fundamentals (Kimball).
• Experience running data infrastructure, with Git-based workflows, CI/CD and code review.

GitLab is all-remote. Location: Bangalore, India.