Intermediate Data Engineer - 85743

Intermediate Data Engineer - 85743

Duration: 1-year contract (possible extension)

Location: Downtown Toronto (3 days onsite)

Department: Global Asset Management

The bank's Global Asset Management Financial Group, backed by a 200-year legacy of trust and innovation. With over $221 billion in assets under management and a diverse suite of investment solutions-including mutual funds, ETFs, and alternative investments the GAM is committed to delivering agile, visionary strategies for institutional, retail, and high-net-worth clients. Our mission is to boldly grow the good in business and life, combining traditional investment wisdom with cutting-edge technology and sustainable practices.

Role Description

• As a Data Engineer, you will design, develop, and optimize data systems and pipelines to support the bank's GAM’s analytics and reporting capabilities. You will work closely with data analysts, BI engineers, and business stakeholders to ensure efficient data flow and enable data-driven decision-making.

Key Responsibilities:

• Design and implement scalable data pipelines and ETL processes.

• Develop and maintain data models and data warehouse infrastructure.

• Collaborate with cross-functional teams to deliver analytic solutions.

• Drive technology modernization and migration projects to modern platforms.

• Optimize performance and reliability of data systems in cloud and on-prem environments.

MUST HAVE

• 5+ years of experience in Data Engineering and ETL development.

• 3+ years' experience with Python and SQL for data processing and automation.

• Solid understanding of Data Modeling, Data Warehousing, and Analytics concepts.

• Familiarity with AWS tools such as SageMaker, AWS Unified Studio, and other data services is highly desirable.

• Proven experience in tech modernization/migration projects.

• Strong problem-solving, communication, and collaboration skills.

Nice to Have:

• Experience with SAS and WebFOCUS for advanced analytics and reporting.

• Exposure to machine learning workflows and data science integration using AWS SageMaker.

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

• Familiarity with CI/CD pipelines for data engineering solutions.

• Hands-on experience with cloud-based data platforms (AWS preferred).

• Banking Industry

Education/certifications: Bachelor’s degree in computer science, Engineering, or a related field.

Interview process

2 rounds; 1st round Teams 30 mins tech & behavioral; 2nd interview in person 30 mins