Address:

Oversees the development of methods, practices, policies, tools and processes to collect, store, access and use data securely, efficiently, and cost-effectively. Supports the full lifecycle of data assets. Assures the quality of data collection, including the adequacy, accuracy and legitimacy of the data. Identifies ways to manage data across a diverse but unified data tier. Plans and supports the implementation of cloud data management platforms and tools, policies and procedures giving the organization control of business data, both in cloud applications and hybrid cloud/ on-premise set-ups. Manages data integration applying relevant data governance and management practices.

• Creates and maintains an optimal data pipeline architecture.

• Assembles large, complex data sets that meet functional / non-functional business requirements.

• Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.

• Builds the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.

• Builds analytics tools that utilize the data pipeline to provide actionable insights into customer, operational efficiency and other key business performance metrics.

• Works with different stakeholders and teams to assist with data-related technical issues and support their data infrastructure needs.

• Works with experts in data strategy and data governance to suggest quality enhancements.

• Operates at a group/enterprise-wide level and serves as a specialist resource to senior leaders and stakeholders.

• Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to problems that can be complex and non-routine.

• Implements changes in response to shifting trends.

• Broader work or accountabilities may be assigned as needed.

Qualifications:

• Typically 15+ years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.

• Bachelor Degree in Computer Science, Data Science, Data Engineering

• 3-5 years experience as a Principal Engineer

• Data architecture design and modeling, AI Engineering, Data Engineering

• Hands-on Coding (Python, Spark, Scala)

• Cloud computing architecture.

• Data security.

• Machine learning, Artificial Intelligence (AI/GenAI), RAG, MLOps, LLMOps

• Computational thinking and programming.

• Deep learning.

• Data integration.

• Data warehousing.

• Big data.

• Streaming / Real time.

• Verbal & written communication skills.

• Analytical and problem solving skills.

• Collaboration & team skills; with a focus on cross-group collaboration.

• Able to manage ambiguity.

• Data driven decision making.

• Stakeholder Management

• Financial Industry experience or FinTech or Technology

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: