AI Machine Learning Data Engineer
Summary
Data Engineer at Scotiabank in Toronto building AI/ML and data engineering solutions: designing Databricks/Spark lakehouse data products, governed Generative AI and agentic solutions, and secure cloud-native applications on GKE using Python and SQL.
Build AI/ML and data engineering solutions as a Data Engineer in Toronto, using Python, SQL, Databricks, and cloud-native technologies.
At Scotiabank, this Data Engineer provides hands-on technical expertise across software engineering, data engineering, and AI/ML. You will shape solution architecture, establish engineering standards, and lead complex delivery from discovery through production. The work includes governed Generative AI patterns, scalable data products, and secure applications on GKE.
Key Responsibilities:
- Design architectures for complex AI, data, and software products
- Lead secure cloud-native applications and service integrations on GKE
- Develop governed Generative AI and agentic solutions
- Architect Databricks, Spark, PySpark, and Lakehouse data products
- Mentor engineers through design reviews and technical coaching
Requirements:
- Degree in a related STEM discipline or equivalent practical experience
- Two or more years of progressive technical production experience
- Advanced Python, SQL, software design, API, and testing skills
- Hands-on Databricks, Spark, PySpark, and Medallion architecture experience
- Experience influencing architecture, security, risk, and business stakeholders
Apply your Python, Databricks, cloud-native, and AI/ML expertise to production engineering at Scotiabank in Toronto.