Data Engineer

Scotiabank • Toronto, ON

1d • Onsite

About The Position

The Data Engineer plays a critical role within the Enterprise Data & AI Technology organization—one of Scotiabank’s most significant enterprise-wide strategic initiatives. This organization drives data enabled decision making, AI innovation, and technology modernization across the Bank.

Requirements

• Experience building data pipelines, and composable cloud-based data platforms (Azure), using Azure Data Factory, ADLS.
• Experience working with Lakehouse platforms: Databricks, Unity Catalog, Auto Loader
• Experience with data engineering, programming, ETL and ELT processes for data extraction and processing
• Experience working with structured, semi-structured, and unstructured data.
• Strong programming and scripting skills (SQL, Python, Java, Scala)
• Strong knowledge of cloud infrastructure and microservices architecture
• Experience in creating technical design documentations, both logical and physical view
• Experience collaborating and working with DevOps, Scrum, and Product Teams
• Demonstrated team player with strong communication skills and a track record of successful delivery of product development.
• Solid communication skills – ability to translate complex technical problems to business language
• Experience in leading and driving technical discussions
• Expert at problem solving and debugging
• 4+ years of experience working with Data Warehouse / Data Platforms
• 4+ years of experience creating ELT / ETL data pipelines, working with structured, semi-structured, and unstructured data
• 4+ years of experience working on continuous integrations and continuous deployment pipeline (CI/CD) and working with source control systems such as Github, Bitbucket, and Terraform
• Must have 4+ years of experience in Cloud: Azure
• Must have 4+ years of experience in Lakehouse: Databricks

Responsibilities

• Design, build, and maintain scalable, resilient data pipelines to support the ingestion, processing, and distribution of large datasets.
• Leverage SaaS platforms and tools to develop, configure, and automate data workflows, improving efficiency across the data engineering lifecycle.
• Partner with stakeholders and product managers to gather requirements, design ingestion patterns, and onboard new data sources into the cloud data platform.
• Implement observability capabilities and continuously optimize application services and pipeline performance.
• Perform data integrity validation to ensure accuracy, reliability, and consistency of data.

Benefits

• Upskilling through online courses, cross-functional development opportunities, and tuition assistance.
• Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
• Free tea & coffee, universal washrooms, and lots of space for team collaboration.
• Opportunities for community engagement & belonging with our various programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed