Data Engineer

Responsibilities Design and build data pipelines/flows for ML use cases Implement data versioning practices Deploy and manage flows in orchestration tools Improve and maintain CI/CD pipelines Manage Python dependencies (Poetry, uv) Deploy data scientists' scripts and models from notebooks to production Implement data quality checks to ensure pipeline reliability Optimize data processing jobs for performance and cost, particularly on distributed systems and cloud data services Qualifications 3–5 years of experience as a Data Engineer Strong proficiency in Python Experience with distributed systems for big data processing (Dask, Spark) Experience building ETL pipelines Experience building reliable, maintainable data pipelines Hands-on experience with GCP core data services (Cloud Storage, BigQuery, Cloud Build, GKE) Experience with orchestration tools (Airflow, Dagster, or similar) Comfortable working in a Linux environment with Jupyter, Python, Git, Docker, SQL, and NoSQL Strong experience with Pandas, SQL, and writing Dockerfiles Professional-level English Nice to have Experience with ML datasets Experience building data pipelines for AI models Experience with LangGraph and RAG systems