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Design, build, and support scalable data pipelines, models, and analytical data products that enable deeper business insights and data-driven decision-making. This role combines hands-on data engineering with business and analytical acumen to integrate complex data sources, automate data preparation, and deliver trusted, well-governed datasets across cloud and hybrid environments.

Key Engineering Responsibilities

• Design, develop, test, and support production-grade data pipelines and analytical data products, transforming data from multiple sources into curated, business-ready datasets.
• Integrate and transform data across databases, APIs, files, enterprise applications, spreadsheets, and approved external data sources.
• Build scalable data models that enable consistent business definitions and support analytics, reporting, and downstream applications.
• Automate recurring data preparation and transformation processes, reducing manual effort and improving the timeliness, consistency, and reliability of data delivery.
• Develop data solutions using Python, SQL, SAS, AWS Glue, Athena, PySpark/Spark, APIs, and cloud-based data services, applying established engineering patterns and standards.
• Embed data-quality and operational controls through validation, reconciliation, exception handling, logging, monitoring, and automated testing.
• Support production data products, monitoring scheduled workloads, troubleshooting failures and data issues, and implementing sustainable solutions.
• Apply modern software-engineering practices, including version control, unit and integration testing, code reviews, CI/CD, documentation, and production-readiness standards.
• Partner with business, analytics, and technology teams to translate requirements into maintainable data models, pipelines, and analytical solutions.
• Support modernization of legacy data and reporting processes, including spreadsheet- and SAS-based workflows, while preserving required business logic and controls.

Investment Data & Analytics

• Develop working knowledge of investment products and structures, including mutual funds, ETFs, pooled funds, segregated mandates, separately managed accounts, fixed income, equities, alternatives, and cash instruments.
• Work across investment and business data domains, including products, clients, accounts, distribution channels, AUM, flows, revenue and fees, holdings, transactions, portfolios, and reference data.
• Build analytical datasets and models that connect product, client, distribution, and investment data to support meaningful business insights.
• Apply business rules and data-quality controls to financial and investment data, identifying inconsistencies and escalating unclear definitions or control gaps.
• Partner with business and data SMEs to understand data meaning, preserve critical business logic, and translate analytical requirements into scalable data solutions.

Required qualifications

• 5+ years of experience in data engineering, analytics engineering, ETL development, or a related discipline, with experience building and supporting production data solutions.
• Bachelor’s degree in computer science, engineering, data, or a related discipline, or equivalent practical experience.
• Strong proficiency in Python and SQL, with hands-on experience in data transformation, automation, validation, performance optimization, and troubleshooting.
• Experience with modern data engineering patterns, including ETL/ELT, data integration, orchestration, relational and dimensional modelling, data warehousing, and distributed data processing.
• Experience integrating data from databases, APIs, files, enterprise applications, and external data sources.
• Experience designing and supporting data models and curated datasets used for analytics, reporting, or downstream applications.
• Hands-on experience with cloud-based data platforms, preferably AWS, or strong experience across enterprise on-premises and hybrid data environments.
• Understanding of data quality, reconciliation, error handling, logging, security, monitoring, and operational controls.
• Experience with Git, automated testing, documentation, and structured software-development practices.
• Strong communication, analytical, problem-solving, and prioritization skills, with the ability to work effectively across technical and business teams.

Preferred qualifications

• Experience in asset management, wealth management, banking, capital markets, distribution analytics, product analytics, or financial and management reporting.
• Working knowledge of investment products and business measures, with the ability to translate analytical questions into reliable datasets and data models.
• Experience with modern data platforms and technologies such as AWS data services, Databricks, Snowflake, Redshift, AWS Glue, Airflow, dbt, Spark/PySpark, Power BI, or comparable technologies.
• Experience modernizing legacy data and reporting solutions, including SAS, TIBCO IBI WebFOCUS, spreadsheet-driven processes, or other legacy platforms.
• Familiarity with CI/CD, APIs, automated testing, data migration, and cloud modernization practices.
• Exposure to AI/ML or advanced analytics workflows and the data engineering patterns that enable them.

What Success Looks Like

• Reliable, well-tested, and maintainable data products that deliver complete, timely, and trusted data for analytics and decision-making.
• Reduced manual data preparation and processing through practical automation and reusable engineering components.
• Consistent and reusable data models that improve how business, client, product, distribution, and investment data is consumed across analytical solutions.
• Fewer data-quality issues and reporting breaks through effective validation, reconciliation, monitoring, and exception handling.
• Strong operational readiness through clear documentation, lineage, monitoring, runbooks, and support practices.
• Growing investment-domain expertise, connecting technical implementation with business context and asset-management outcomes.

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.