Job Summary

We are seeking an experienced Lead Data Business Analyst to support the BMO Global Asset Management (BMO GAM) business as part of the Investment Solutions and Delivery team. In this role, you will drive the end-to-end delivery of data-centric investment solutions, from requirements gathering and documentation through data analysis, testing, and final implementation, ensuring solutions enable accurate, timely, and fact-based investment and business decisions.

Location: Address: VIRTUAL(R)59 - REMOTE/TELETRAVAIL - ON - BMO

Key Responsibilities

Requirements Gathering & Documentation

- Leads requirements gathering sessions with Portfolio and/or Product Managers, Investment Operations, Risk, Compliance, Institutional Sales, Technology, and other stakeholders to understand business objectives, pain points, and data needs.
- Translates business objectives into clear business requirements documents (BRDs), functional specifications, user stories, and acceptance criteria for investment solutions.
- Documents current- and future-state business processes, data flows, control points, dependencies, and operational procedures, and keeps them up to date.
- Maintain end-to-end traceability from approved business outcomes and requirements through data rules, solution design, test cases, defects, implementation evidence, and final business acceptance.
- Assess proposed solutions against the underlying business objective and challenge approaches that do not adequately satisfy approved requirements.

Data Knowledge & Management

- Serves as a subject-matter expert on investment data, including securities, holdings, transactions, performance, benchmarks, reference data, and related investment datasets.




- Develops and maintains source-to-target data mappings, data dictionaries, business rules, transformation requirements, and supporting data documentation.
- Documents end-to-end data lineage from external and internal sources through to downstream reporting and analytics, supporting data governance, controls, and auditability.
- Perform root-cause analysis of data discrepancies, process breaks, and control issues, working across business, operational, technical and vendor interests to determine underlying causes and appropriate remediation.
- Analyzes, profiles, and reconciles data from multiple sources using SQL and Python to identify gaps, data quality issues, and root causes, enabling more efficient processes and streamlined reporting.
- Structures data into multiple dimensions and granularities (e.g. products, positions, transactions) to support reporting and analytics.
- Rationalizes legacy data sources, ensuring explicit stewardship, proper documentation, reduction of technical debt, and alignment with modern data architecture principles.

Testing & Quality Assurance

- Plans and coordinates user acceptance testing (UAT), including test strategy, test scenarios, test cases, and test data, and obtains business sign-off prior to production release.




- Validates data outputs against requirements and source systems and automates validation tests where possible to improve quality and efficiency.
- Logs, tracks, and manages defects through to resolution in partnership with technology teams and vendors.
- Assesses proposed defect resolutions and workarounds for their impact on business requirements, data quality, operational processes, control, and downstream consumers.
- Maintain clear traceability between requirements, testing evidence, identified defect, remediation, and business acceptance.

Solution Delivery

- Supports the design, development, and implementation of data, analytics, and reporting solutions aligned with business strategy and stakeholder needs.
- Coordinates release readiness, production deployment, and post-implementation validation to ensure solutions are delivered as intended, on time and within scope.
- Conducts pre- and post-implementation analyses to measure business impact, and monitors solution performance from an end-to-end perspective.
- Designs reports, dashboards, and visualizations in Power BI and other visualization tools, and develops training materials and user guides to enable self-serve analytics for business users.

Stakeholder Liaison

- Serves as the trusted data partner and liaison between Investment teams, Investment Operations, Risk, Compliance, Institutional Sales, Technology, Data Platform teams and other business areas ensuring alignment on scope, priorities, timelines, and deliverables.
- Work with external stakeholders, including custodians, fund administrators, market data vendors, and technology providers, on data requirements, issues, and changes.
- Challenge external provider requirements, mappings, solution assumptions, proposed workarounds, t

📌 Data Business Analyst Lead (Montreal)
🏢 Bank of Montreal
📍 Montreal