Build data pipelines with Python, PySpark, and Snowflake while transforming large-scale datasets through distributed processing. Apply deep SQL expertise to reliable engineering work.

This Data Engineer role focuses on Python programming, PySpark transformations, and Snowflake development. You will create ETL and ELT solutions, integrate data, and support migration and orchestration. The work also involves data warehousing, schema design, validation, and error handling.

Key Responsibilities:

- Develop data processing solutions using Python libraries
- Transform large-scale datasets with PySpark
- Build ETL and ELT data integration pipelines
- Design Snowflake tasks, streams, stages, and Snowpipe workflows
- Implement incremental loads, validation, and error handling

Requirements:

- Robust Python experience with Pandas and NumPy
- Strong PySpark experience for distributed data processing
- Extensive SQL knowledge, including joins and window functions
- Hands-on ETL, migration, and pipeline orchestration experience
- Experience with Git, debugging, and code deployment

Use Python, PySpark, SQL, and Snowflake expertise to engineer scalable data processing and integration pipelines.

📌 Python PySpark Data Engineer (Montreal)
🏢 LanceSoft
📍 Montreal