Machine Learning Engineer jobs in Canada

Our client, a leading financial institution in Downtown Toronto, is looking for a Senior Data Engineer to work with business stakeholders and cross-functional teams to understand data requirements and deliver scalable data solutions. The successful candidate will have the opportunity to work with one of the Top 5 Banks in Canada.

• Design, develop, and maintain robust ETL processes to extract, transform, and load data from various sources into our data platform.
• Build large-scale batch and event-driven data pipelines using cloud and on-premises hybrid data platform topology.
• Work closely with data architects to review solutions and data models and ensure adherence to data platform architecture guidelines and engineering best practices.
• Take ownership of end-to-end deliverables and ensure high-quality software development while fulfilling all operational and functional requirements promptly.
• Implement and enforce data quality standards and best practices while collaborating with data governance teams to ensure compliance with data policies and regulations.
• Optimize data integration workflows for performance and reliability.
• Troubleshoot and resolve data integration and data processing issues.
• Leverage best practices in continuous integration and delivery using Data Ops pipelines.
• Apply design-thinking and agile mindset in working with other engineers and business stakeholders to continuously experiment, iterate, and deliver on new initiatives.
• Stay informed about emerging technologies and trends in the data engineering domain.
• Lead, mentor, and inspire a team of data engineers to achieve high performance levels.

• 5-7 years of experience building batch and real-time data pipelines leveraging big data technologies and distributed data processing using Spark, Hadoop, Airflow, NiFi, and Kafka.
• Proficiency in writing and optimizing SQL queries and at least one programming language like Python and/or Scala.
• Experience with cloud-based data platforms (Snowflake, Databricks, AWS, Azure, GCP).
• Expertise using CI/CD tools and working with Docker and Kubernetes platforms.
• Experience with the following DevOps and agile best practices.
• Experience with data modelling tools and methodologies.

• Experience with OpenShift, S3, Trino, Ranger and Hive
• Knowledge of machine learning and data science concepts and tools.
• Knowledge with BI & Analytics tools such as Tableau and Superset

Finance professional is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. We advocate for you and welcome anyone regardless of race, color, religion, national origin, sex, physical or mental disability, or age.