Original job description
Application Deadline: November 30, 2026
Address: 4100 Gordon Baker Road
Job Family: Technology
Salary: $70,000–$150,000 per year
Pay Type: Salaried
About The Company
BMO Financial Group is driven by a shared purpose: Boldly Grow the Good in business and life. We work to create lasting, positive change for our customers, communities, and employees. Through collaboration, innovation, and a commitment to pushing boundaries, BMO supports businesses, contributes to economic growth, and helps people and organizations reach their goals.
Data and AI Technology (DAT) Engineering supports BMO’s digital-first strategy and its risk, regulatory, and compliance requirements. The team builds data and AI products that deliver timely, actionable insights and help business partners make informed, data-driven decisions. Working across the bank, DAT Engineering contributes to hundreds of initiatives each year, addressing complex challenges and creating business value.
About The Role
Join a diverse engineering organization where you can apply your technical skills to complex business problems and work with evolving data and AI technologies. In this role, you will lead the planning, design, development, testing, implementation, documentation, and support of data and AI products. You will work closely with business stakeholders to understand functional and non-functional needs, translate them into technical solutions, and help ensure those solutions align with established standards and technology roadmaps.
You will also contribute to stronger engineering practices by developing reusable frameworks and automation, improving delivery and deployment processes, and supporting the growth of colleagues through mentoring and knowledge sharing.
Qualifications
You bring five to seven years of relevant experience, supported by IT education, certifications, or equivalent professional expertise. You have hands-on experience in ETL/ELT development and testing, data warehousing, and working with SQL, NoSQL, Python, Spark, and Scala. Your background includes technologies such as SSIS, AWS Glue, cloud storage and computing services in AWS or Azure, Hadoop, and Netezza.
You are comfortable working with structured, semi-structured, and unstructured data in both batch and streaming environments. You have experience in data analysis, data mapping, and data profiling, along with an understanding of AI concepts, generative AI, prompt engineering, retrieval-augmented generation (RAG), and AI-enabled tools in the software development lifecycle. Familiarity with Agile delivery and JIRA is required. Experience in a large enterprise, working with senior leaders, or operating in a highly regulated industry is an asset.
Responsibilities
Lead the end-to-end delivery of data and AI products, from planning and technical design through development, testing, implementation, documentation, and ongoing support. Partner with business stakeholders to clarify requirements and shape reliable, practical solutions. Provide technical direction on designs and confirm alignment with standards, architecture, and roadmaps.
Guide junior and intermediate developers, identify and track defects, and perform regression testing to verify fixes. Find opportunities to improve engineering workflows, delivery practices, and deployment capabilities. Build automation scripts, frameworks, and reusable code to accelerate development and improve consistency. Strengthen team capability through mentoring, knowledge sharing, and communities of practice.
Benefits
BMO offers a total compensation package that may include performance-based incentives, discretionary bonuses, and other rewards, depending on the position and pay type. Benefits include health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. Compensation may vary according to location, skills, experience, education, and qualifications. Part-time compensation is prorated based on regular hours worked. The stated salary range represents BMO Financial Group’s pay range for this salaried position.
BMO supports employee growth through training, coaching, manager support, and opportunities to build professional networks and broaden skills.
Equal Opportunity
BMO Financial Group is committed to an inclusive, equitable, and accessible workplace. We value the perspectives and strengths people bring through their differences. Accommodations are available upon request for candidates participating in any part of the selection process; please contact your recruiter to request support.
More about this job
Responsibilities
Lead end-to-end delivery of data and AI products, including planning, design, development, testing, implementation, documentation, and ongoing support. Partner with business stakeholders, guide developers, ensure alignment with technical standards, and improve engineering workflows through automation, reusable frameworks, mentoring, and knowledge sharing.
Requirements
Requires five to seven years of relevant experience, supported by IT education, certifications, or equivalent professional expertise, with hands-on experience in ETL/ELT, data warehousing, and the listed data technologies. Candidates should also understand structured and unstructured data, batch and streaming environments, AI and generative AI concepts, RAG, Agile delivery, and JIRA.
Skills
- ETL/ELT Development
- Data Warehousing
- SQL
- NoSQL
- Python
- Spark
- Scala
- SSIS
- AWS Glue
- AWS
- Azure
- Hadoop
- Netezza
- Data Analysis
- Data Mapping
- Data Profiling
Benefits
- Health Insurance
- Tuition Reimbursement
- Accident Insurance
- Life Insurance
- Retirement Savings Plans
- Performance-Based Incentives
- Discretionary Bonuses
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Engineering
- Finance & Accounting
Keywords
- Data Engineering
- Data And AI Products
- ETL/ELT
- Data Warehousing
- SQL
- NoSQL
- Python
- Spark
- Scala
- SSIS
- AWS Glue
- AWS
- Azure
- Cloud Storage
- Cloud Computing
- Hadoop
- Netezza
- Batch Processing
- Streaming
- Data Analysis
- Data Mapping
- Data Profiling
- Artificial Intelligence
- Generative AI
- Prompt Engineering
- Retrieval-Augmented Generation
- Agile
- JIRA
- Automation
- Regression Testing
