Intermediate Data Engineer (Fully Remote)

GitLab; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

GitLab is seeking a data platform engineer to build and maintain ELT pipelines and infrastructure for GitLab's data platform. You will power reporting, data science, and AI self-service with reliable, governed data.

You will develop pipelines in Python and SQL, manage Snowflake, Airflow, and Kubernetes; triage failures, monitor SLAs, ensure data quality and cost-efficiency; and use AI coding agents daily while maintaining rigorous review standards.

Qualifications

• Develop pipelines in Python and SQL; manage Snowflake, Airflow, and Kubernetes.
• Triage failures, monitor SLAs, and ensure data quality and cost-efficiency.
• Use AI coding agents daily while maintaining rigorous review standards.

Responsibilities

• Build and maintain ELT pipelines and infrastructure for GitLab's data platform.
• Power reporting, data science, and AI self-service with reliable, governed data.

Skills

Python

SQL

Snowflake

Airflow

Kubernetes

Data governance

Job description

• Build and maintain ELT pipelines and infrastructure for GitLab's data platform.
• Power reporting, data science, and AI self-service with reliable, governed data.

Key Responsibilities:

• Develop pipelines in Python and SQL; manage Snowflake, Airflow, and Kubernetes.
• Triage failures, monitor SLAs, and ensure data quality and cost-efficiency.
• Use AI coding agents daily while maintaining rigorous review standards.

Team & Culture:

• Fully remote, asynchronous collaboration via issues and merge requests.
• High-performance culture driven by values and continuous knowledge exchange.

GitLab

GitLab is the intelligent orchestration platform for DevSecOps, helping organizations increase developer productivity and accelerate digital transformation. With over 50 million registered users and a high-performance, AI-first culture, GitLab is fully remote and values-driven.