Lead GCP Data Engineer

Canada Remote

We are looking for a skilled and motivated Lead Data Engineer with strong expertise in Python, PySpark, and Pandas, along with hands-on experience in Google Cloud Platform (GCP) services. The ideal candidate should have a deep understanding of data warehousing concepts, dimension modeling, and SQL, with proven experience building and supporting enterprise-level data solutions in a cloud environment..

Key Responsibilities:

• Design, develop, and maintain data pipelines and ETL workflows using Python and PySpark.

• Build and manage Enterprise Data Warehouses and Data Marts, ensuring high performance and scalability on GCP.

• Work on descriptive analytics and reporting by transforming and querying data using BigQuery SQL.

• Conduct peer code reviews, contribute to technical design documents, and help write unit tests and integration test cases.

• Collaborate with business analysts and stakeholders to understand data requirements and ensure data accuracy.

• Support, monitor, and troubleshoot data pipelines and systems in a production environment.

• Participate in deployment and CI/CD processes using GIT and GCP DevOps tools.

• Maintain detailed documentation and contribute to a knowledge repository for team enablement and capability building.

• Demonstrate strong problem-solving and communication skills in a fast-paced, collaborative setting.

• Stay updated with evolving cloud technologies and suggest improvements to enhance performance and efficiency.

Required Skills & Qualifications:

• 6+ years of experience working with Python, PySpark, and GCP.

• Hands-on experience with data transformation, data quality checks, and data validation in large-scale systems.

• Strong expertise in SQL (including advanced SQL concepts) and data warehousing methodologies.

• Hands-on experience with BigQuery, DataProc, and Cloud Storage in GCP.

• Understanding of dimensional modeling, star/snowflake schemas, and data marts.

• Experience with data validation, data quality, and ETL automation in large-scale environments.

• Relevant GCP certification (e.g., Google Professional Data Engineer) is preferred.

• Familiarity with version control systems like GIT and CI/CD processes