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Intermediate Data Engineer
DataRemote — Bangalore, India
Published on 2026-11-02
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Build and operate reliable data pipelines and infrastructure that power GitLab’s analytics, data science, and AI use cases. Own features end to end, from source integration through testing, monitoring, and documentation, while ensuring data remains secure, governed, and cost-efficient.
About the company
GitLab is a DevSecOps platform that brings source control, CI/CD, security, and project management into a single application. It helps engineering teams plan, build, secure, and ship software faster.
The team
Data Platform team within Enterprise Data; reports to the Director, Data Platform.
Stack
PythonSQLSnowflakeFivetranMonte CarloAirflowKubernetesdbt
What you'll do
- Build and maintain ELT pipelines from enterprise applications, internal systems, and GitLab SaaS.
- Manage data platform infrastructure, including SaaS tools and self-managed services.
- Triage pipeline failures and infrastructure issues; maintain reliability, data quality, and cost efficiency.
- Partner with analytics, data science, governance, and business teams on downstream data needs.
- Use AI coding agents for development, debugging, testing, and documentation while maintaining review rigor.
- Apply access controls and masking policies to make governed data safely available to AI tools and agents.
- Ship iterative features, review merge requests, and document architecture and runbooks.
What we're looking for
- Production data pipeline experience in Python.
- Strong SQL skills and experience with a cloud data warehouse.
- Experience with scalable ETL or ELT, incremental loads, schema changes, backfills, and API ingestion.
- Experience with orchestration tools such as Airflow; familiarity with dbt and dimensional modeling.
- Experience troubleshooting data infrastructure and using Git workflows, CI/CD, and code review.
- Hands-on daily use of AI coding tools and understanding of their limitations.
- Clear written communication and comfort working asynchronously in a fully remote organization.
Nice to have
- Snowflake experience or administration.
- Docker, Kubernetes, Google Cloud Platform, or Terraform experience.
- Experience with Salesforce, Zuora, or Zendesk APIs.
- Data observability tooling experience.
Benefits
- Flexible paid time off
- Equity compensation and employee stock purchase plan
- Growth and development fund
- Parental leave
- Team member resource groups