Data Management

In a changing world, unprecedented challenges require unmatched talent. Join one of Montreal's Top Employers in 2025. We are a dynamic and growing organization having its main establishment located in downtown Montreal and part of a leading international banking institution fully committed to building a more sustainable future. Note that the position may be in the Canadian Branch of BNP Paribas or in one of its subsidiaries based in Montreal.

**The position at a glance**

The Data Office Department drives and continuously improves the way data is handled throughout the organization. It looks to satisfy the requirements related to principles for effective enterprise data aggregation and reporting and is intended to support evolving regulatory requirements.

The Data Office Department is made up of the following 5 pillars:

- Data Governance: set the framework for developing and formalizing the “know your data” culture including formal governance forums
- Data Management: determine the data strategy for the platform with the objective of identifying and adopting golden sources, capturing, and maintaining data glossaries and dictionaries, business, and functional lineage from source to output as well as managing referential data
- Data Quality: Set up a framework to assess and report on the data used for reporting purposes and an effective remediation team and data certification and attestation processes
- Data Solutions: develop various types of value-added solutions using data
- Data Privacy and protection: protect personal information of clients, employees, and other individuals from third parties

**In detail**

The team members are responsible for the following activities:
The analyst will be contributing across the data office, depending on priority. The activities and responsibilities of the analyst may be performed in a project or BAU mode:
**Data Management & Quality**
- Plan, launch, and sustain data‑management & data‑quality initiatives - develop project charters, scopes, timelines, and success criteria; track progress against milestones.
- Oversee data‑quality monitoring & reporting - create a repeatable issue‑tracking workflow, generate status reports and dashboards that highlight inconsistencies, inaccuracies, and anomalies for internal/external processes.
- Define and enforce data‑validation rules - facilitate cross‑functional workshops with Business Analysts, IT, and Data Owners/Stewards; translate requirements into test cases and automated checks and certify data fitness before it’s used for reporting or decision‑making.
- Build and maintain data‑quality KPI dashboards - design visual dashboards (Power BI, Tableau, etc.) to track accuracy, completeness, timeliness, and other dimensions; set alerts for SLA breaches and produce regular performance reports.
- Coordinate issue resolution across teams - establish a RACI matrix, hold regular stand‑ups/steering‑committee meetings, assign owners, and monitor remediation tasks in the project‑management tool (e.g., Jira, Azure DevOps).
- Manage metadata and data lineage - lead a metadata‑cataloguing project to document data sources, transformations, and downstream usage; schedule periodic lineage reviews and updates.
- Support data‑integration projects - scope inbound data feeds, define quality gates, run integration test suites, and report readiness status to stakeholders.
- Identify data‑related risks and drive mitigation - conduct risk assessments at project kickoff, log risks in a register, and implement mitigation or contingency plans.
- Deliver training and knowledge‑transfer programs - create targeted workshops/e‑learning on data‑quality standards, validation tools, and governance processes; track uptake and competency metrics.
- Drive continuous‑improvement and automation and prioritize enhancements in a project backlog.
- Produce project artefacts and documentation - maintain up‑to‑date project plans, risk/issue registers, status dashboards, and lessons‑learned logs to ensure transparency and repeatable success.

Staff supervision/ Organizational Structure:
The Analyst will report to the Head of Metadata (Data Management) and will be working with local and global teams.

**The strengths and skills that will help you succeed**

**EDUCATION**:

- Bachelor’s degree in Computer Science, Information Management, Data Science, Business Administration, or a related field.
- A relevant certification (e.g., PMP, PRINCE2, Agile/Scrum) is a good to have.

**Years of experience**:

- 5-7 plus years of professional experience ideally in data management or Project Management role in IT

**Languages**:

- Professional working proficiency in English*

**Technical skills**:

- Collibra, Power Bi, Project Management tools, Microsoft Office (Word, Excel, PowerPoint)

**Soft skills**:

- Effective communication & stakeholder engagement.
- Project management leadership.
- Autonomous execution.
- Analytical and problem solving, with a keen sense for processes improv