Senior Data Engineer to develop and modernize data pipelines using Google Cloud Platform (GCP)- 40709

Our financial services client is seeking a Senior Data Engineer to develop and modernize data pipelines using Google Cloud Platform (GCP)- 40709

Location: Toronto/Hybrid: 2 days in-office

Contract Duration: 06/29/2026 to 10/31/2026 (High Chance of Extension)

Schedule Hours: 9am-5pm Monday-Friday; standard 37.5 hrs/week.

Story Behind the Need

• Business group: International Banking Technology Transformation (IBTT)

• Project: Data Platform Modernization project.

Setting up data pipeline to ingest large volumes of data from multiple on-premise applications into Google Cloud Platform (GCP).

Reason: Backfill to the contractor who moved to FTE.

SUMMARY:

RESPONSIBILITIES:

• Champions a client centric culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.

• Functions as a member of an agile team and helps drive consistent development practices, tools usage, common components, and patterns.

• Collaborates with cross functional stakeholders to build scalable data ingestion pipelines and improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making.

• Performs hands-on design and development with SQL/BigQuery/PySpark/Pandas, Parquet/ORC/Avro file formats processing, using appropriate data ingestion patterns, data modelling techniques and Airflow scheduling / orchestration.

• Setup ingestion pipeline using medallion framework and automate Data Quality validation processes.

• Perform testing, debugging and troubleshooting to support BAU operations and continuous improvements.

• Direct the identification and recommendation of appropriate solutions, and guide junior team members.

• Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions.

Candidate Requirements/Must Have Skills:

• 8-10 years of relevant work experience

• 5+ years of experience in data engineering, including ETL/ELT development, data modeling, data quality, and governance.

• Proven experience designing and implementing cloud data solutions (GCP and/or Azure).

• 2+ years of experience leading or mentoring engineering teams.

• Strong hands-on experience with Python, Spark, Airflow, and advanced SQL.

• Solid understanding of data warehousing concepts, schema design, and analytical data models.

• Skilled in dimensional modeling and Cloud architectures

• Experience with CI/CD pipelines, version control (Git), and Infrastructure as Code.

• Knowledge of cloud security, data governance, and regulatory compliance in financial environments.

Nice-To-Have Skills:

• Prior experience working in a regulated financial services or banking environment, supporting cloud migration or modernization initiatives.

• Experience working with Enterprise Data Lakes and Hadoop (HDFS/Hive)

Degrees or certifications:

• Bachelor's degree in a related field required

• GCP Professional Data Engineer certification is nice to have

Best vs. Average Candidate:

The ideal candidate would be an experienced Data Engineer with previous experience with Data modernization projects and recent experience with GCP. Previous experience with Top 5 Banks is highly preferred.

Candidate Review & Selection

1 Round of interviews: With HM and another senior engineer.

Structure and Format: MS Teams Interview - 1 hour.