Data Engineer

📋 Description

• Develop, schedule, and monitor ELT/ETL pipelines in Python to ingest data from APIs, files, and
• Implement transformations (SQL & Python) following modular, reusable patterns.
• Leverage AI-assisted tooling (e.g., GitHub Copilot) to accelerate development, improve readability
• Build tables, views, stages, and secure data shares in Snowflake.
• Tune queries and warehouse configs; manage roles, RBAC, and resource usage.
• Use AI assistance to analyze query performance, refactor SQL, and identify optimization

🎯 Requirements

• 3–5 years of experience in data engineering, analytics engineering, or backend engineering
• Programming: Python (pandas, SQLAlchemy/DB APIs, typing, testing with pytest).
• SQL & Warehousing: Strong SQL; experience with Snowflake (warehouses, stages, tasks, Snowpipe
• Cloud Basics: Familiarity with one major cloud (AWS/Azure/GCP) and storage + compute + IAM
• DevSecOps Mindset: Git, CI/CD (GitHub Actions/Azure DevOps/GitLab CI), code reviews, secret
• Data Quality: Exposure to unit tests, data validation (e.g., Great Expectations/dbt tests), and

🎁 Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)