Job Description

GCP Technical Lead - 10+ Years

Location

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Toronto, ON

Mode of Work : Hybrid (4 days a week)

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Role Overview:

We are looking for a skilled GCP Data Engineer with strong experience in building and optimizing data pipelines on Google Cloud Platform. The ideal candidate will have hands-on expertise in ETL workflow design using Spark Serverless and Spark on GKE, combined with proficiency in Python programming for data processing and automation. This role requires deep knowledge of GCP services, data governance, and monitoring practices.

Key Responsibilities:

Data Pipeline Development:



Design, develop, and maintain scalable ETL workflows using Spark Serverless, Spark on GKE, and Python. Implement data ingestion, transformation, and loading processes for structured and unstructured data.

Cloud Architecture & Optimization:



Utilize GCP services such as BigQuery, CloudSQL, Cloud Storage, and Pub/Sub for efficient data processing. Optimize performance and cost for large-scale data workflows.

Data Governance & Quality:



Implement frameworks for data governance, data quality checks, and data lineage tracking, preferably using GCP tools. Ensure compliance with organizational and regulatory standards.

Monitoring & Logging:



Set up Cloud Logging, Cloud Monitoring, and alerting for data pipelines and infrastructure. Troubleshoot and resolve issues proactively to maintain high availability.

Collaboration & Automation:



Work closely with data scientists, analysts, and architects to deliver reliable solutions. Automate workflows and processes using Python and GCP-native tools.

Required Skills and Qualifications:

Strong experience with Google Cloud Platform and its data services. Hands-on expertise in Spark Serverless, Spark on GKE, and Python programming. Proficiency in BigQuery, CloudSQL, and GCP-native ETL tools. Knowledge of data governance, data quality frameworks, and lineage tools. Experience with Cloud Logging, Cloud Monitoring, and observability best practices.

Preferred Qualifications:

GCP Professional Data Engineer certification. Experience with containerization (Docker/Kubernetes) and CI/CD pipelines. * Familiarity with data security and compliance standards (GDPR, HIPAA, etc.)