Senior Analyst, Data Foundations and Infrastructure

Posted 2 Days Ago
Be an Early Applicant
Toronto, ON, CAN
In-Office
56K-120K Annually
Senior level
Financial Services
The Role
Executes revenue data reconciliations across financial systems and data platforms, investigates variances, validates data quality, and supports recurring pipelines. Uses SQL and Python for data extraction, transformation, automation, and troubleshooting. Develops operational reporting, documents data flows and reconciliation procedures, improves processes, and collaborates with finance, business, engineering, and analytics stakeholders to resolve data issues and enhance Commercial Banking data infrastructure.
Summary Generated by Built In

Application Deadline:

10/30/2026

Address:

250 Yonge Street

Job Family Group:

Data Analytics & Reporting

About the Opportunity:

This is an exciting opportunity to join Commercial Banking's Data Foundations & Infrastructure team and play a key role in maintaining the accuracy, quality, and integrity of the data that powers reporting, analytics, and business decision-making across Commercial Banking.

The team sits at the intersection of business and technology, supporting foundational Commercial Banking datasets across Canada and the U.S. The successful candidate will combine financial acumen, strong SQL capabilities, and data analysis skills to investigate data discrepancies, perform reconciliations, improve operational processes, and support ongoing enhancements to Commercial Banking's data environment.

This role is ideal for someone who enjoys solving complex data problems, understanding the business meaning behind data, and contributing to process improvements that drive operational efficiency. It offers excellent exposure to Commercial Banking data, financial systems, data infrastructure, and broader Data & Analytics initiatives across the organization.

BMO Commercial Bank Data Foundations team is focusing on revenue data reconciliation, processing, and operational data workflows. The role involves executing and improving recurring processes, ensuring data integrity, and supporting finance and business stakeholders.

Core Responsibilities

  • Executes and supports end-to-end revenue data processes, including monthly/periodic reconciliation, investigation, and adjustment workflows across multiple data sources.
  • Performs data reconciliation between financial systems and internal data platforms, identifying variances, root causes, and required adjustments to ensure accuracy and completeness.
  • Writes and maintains SQL queries and Python scripts to extract, transform, validate, and reconcile data across systems.
  • Supports the execution, monitoring, and troubleshooting of recurring data pipelines and batch processes, ensuring timely delivery of revenue datasets.
  • Works closely with finance and business teams to understand data discrepancies, validate outputs, and resolve issues in a timely manner.
  • Identifies opportunities to automate and streamline manual reconciliation and reporting processes using SQL, Python, and other workflow tools.
  • Develops and maintains operational reporting and dashboards to track reconciliation status, data quality, and process performance.
  • Documents data flows, reconciliation logic, and operational procedures to support transparency, auditability, and onboarding.
  • Ensures adherence to data quality standards (accuracy, completeness, consistency, timeliness) within revenue datasets.
  • Collaborates with data engineers and analytics teams to enhance data models and improve processing efficiency.
  • Provides ongoing support to business stakeholders by investigating data issues and responding to inquiries related to revenue data.

Qualifications

Must-have Skills

  • Strong hands-on experience with SQL (required) – ability to query, join, and troubleshoot large datasets
  • Experience with Python (required) for data processing, automation, or scripting
  • Working knowledge of data reconciliation, data validation, or data quality processes
  • Basic understanding of accounting principles (e.g., revenue, GL, reconciliations)

Good-to-have

  • Experience supporting financial or revenue data processes in banking or financial services
  • Familiarity with ETL/data pipelines
  • Experience with data quality frameworks or controls
  • Exposure to month-end or periodic processing cycles

Core Competencies

Foundational:

  • Data reconciliation & validation
  • Data operations & process execution
  • SQL & data manipulation
  • Systems thinking
  • Problem solving

Intermediate:

  • Process improvement & automation
  • Stakeholder communication (finance + business)
  • Analytical thinking & root cause analysis
  • Documentation & operational governance

Experience

  • Typically, 1–3 years of relevant experience in data analytics, data operations, or financial data roles
  • Experience working with large, complex datasets and operational processes
  • Background in banking, finance, or revenue data environments preferred

Salary:

$55,500.00 - $120,000.00

Pay Type:

Salaried

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.

Skills Required

  • Strong hands-on SQL experience, including querying, joining, and troubleshooting large datasets
  • Python experience for data processing, automation, or scripting
  • Working knowledge of data reconciliation, data validation, or data quality processes
  • Basic understanding of accounting principles, including revenue, general ledger, and reconciliations
  • Typically 1–3 years of relevant experience in data analytics, data operations, or financial data roles
  • Experience working with large, complex datasets and operational processes
  • Experience supporting financial or revenue data processes in banking or financial services
  • Familiarity with ETL or data pipelines
  • Experience with data quality frameworks or controls
  • Exposure to month-end or periodic processing cycles

BMO Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BMO and has not been reviewed or approved by BMO.

  • Parental & Family Support — Paid parental leave up to 16 weeks at full pay for all new parents, plus up to $20,000 for adoption, surrogacy, and fertility, and 10 days of paid backup childcare indicate robust family support. These elements stand out within BMO’s U.S. package.
  • Retirement Support — A 401(k) design combining a core employer contribution with dollar-for-dollar matching up to a set portion of pay, plus immediate vesting on match and employee contributions, signals strong retirement funding. The core contribution’s three-year vesting is clearly defined.
  • Leave & Time Off Breadth — Vacation accrual scales with grade and service, alongside 9–10 paid holidays and additional paid time off buckets (bereavement, school activities, civic duties, blood donation, volunteering). This breadth offers multiple avenues for time away beyond standard vacation.

BMO Insights

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The Company
HQ: Toronto, Ontario
51,885 Employees

What We Do

At BMO, banking is our personal commitment to helping people at every stage of their financial lives. The truth is, people’s needs change: so we change too. But we never change who we are. Which means we’ll never waiver from providing our customers the best possible banking experience in the industry. Our incredible team of over 46,000 people is just the tip of the iceberg. You should get to know us. We’re here to help.

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