Analytics Engineer, Global Analytics Operations

Scotiabank • Toronto, ON

1d • Onsite

About The Position

The Global Analytics Operations team at Scotiabank is focused on maintaining, stabilizing, and improving cloud-based data platforms so the bank can make data-driven decisions. The team combines strong expertise in data engineering, analytics, and computer science to deliver scalable, reliable solutions. With a strong focus on operational excellence, it drives high pipeline reliability, proactive monitoring, and timely issue resolution while continuously enhancing processes, improving user experience, and introducing new analytical patterns through close collaboration with cross-functional partners.

Requirements

• Bachelor’s or Graduate degree in Computer Science, Engineering, or related field (or equivalent experience)
• Strong experience in SQL (advanced to expert level), Python, and ETL/ELT pipeline development
• Hands-on experience with cloud platforms (GCP, AWS, or Azure) and modern data stack tools (including dbt)
• Experience with workflow orchestration tools such as Apache Airflow
• Solid understanding of data warehousing concepts and dimensional modeling
• A high-performing, detail-oriented, and proactive mindset with strong ownership in handling user requests and troubleshooting issues, and driving continuous improvement initiatives

Nice To Haves

• Knowledge of the banking/finance domain and data governance practices is an asset

Responsibilities

• Support operational excellence through monitoring, incident management, and continuous process improvement
• Own user requests and data inquiries while actively experimenting, learning, and driving continuous improvement in day-to-day operations
• Proactively identify gaps and implement scalable improvements, including new analytical patterns and automation to optimize workflows
• Support analysts and data scientists with reliable, timely, and accessible data, while using AI/agent-based solutions to automate and optimize time-consuming processes
• Partner with business teams to understand data needs and deliver actionable insights to management and stakeholders
• Build and maintain scalable data models and ETL/ELT pipelines
• Maintain data quality through automated testing, monitoring, and proactive issue resolution
• Apply data governance, security, and documentation standards across pipelines and architecture

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level