Required Skills Leadership: Experience leading data engineering teams onshore and offshore.

This is a lead position, not a senior data engineer position.

Candidates without leadership experience will not be considered for this role.

Technical: Proficiency in SQL, Python, Java/Scala, and distributed systems (Spark, Beam). GCP Expertise: Hands-on with Big

Query, Dataflow, Dataproc, Pub/Sub, Composer (Airflow), and Terraform.

Dev

Ops: Familiarity with CI/CD, Git, and infrastructure-as-code.

Nice to Have GCP Certifications (e.g., Qualified Data Engineer).

Experience with real-time processing, Vertex AI, or multi-cloud environments.

Key Responsibilities: Pipeline Development: Build and optimize ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Functions.

Data Infrastructure: Architect and manage Big

Query,



Cloud Storage, and Data Fusion for efficient data ingestion, transformation, and storage.

Team Leadership: Lead a team of 10 engineers, review code, establish data engineering standards, CI/CD, and monitoring (e.g., Cloud Monitoring, Logging).

Performance & Cost: Optimize pipeline performance, query efficiency, and GCP cost management (e.g., slot reservations, partitioning).

Collaboration: Work with data architects, scientists, and analysts to deliver self-service data platforms and support advanced analytics/ML use cases.

Data Quality & Governance: Implement data validation, lineage, and metadata management (e.g., Data Catalog, dbt).

📌 GCP Senior Data Engineer (Toronto)
🏢 J M Group
📍 Toronto