Finance Business & Data Analyst-Hybrid-Montreal, QC

Finance Business & Data Analyst

Montreal, QC

12 Months

The position at a glance

The Financial Data Office (FDO) under FCOO ensures the integrity, usability, and regulatory compliance of financial and operational data across BNP Paribas. It operates through three key pillars to drive data excellence:

• DI&C (Data Integrity & Control): Ensures data accuracy, consistency, and adherence to standards.
• DS&R (Data Stewardship & Remediation): Addresses data quality issues, performs root cause analysis, and oversees end-to-end remediation.
• DS&I (Data Solutions & Innovation): Develops and implements data-driven solutions to enhance efficiency and innovation.

This role falls under DI&C and supports DS&R and DS&I initiatives by focusing on data quality rule creation, SQL development, and business requirement translation for the Deployment of Data Quality Rules (DQRs) across platforms.

In detail

Role Overview

The Finance Business & Data Analyst will be a key contributor to the FDO team in Montreal, focusing on the hands-on development of SQL scripts and the implementation of Data Quality Rules (DQRs) for the systems used by the Finance and Tax departments. This role ensures service continuity by assisting in the deployment of rules, maintaining documentation, and translating business requirements into technical logic.

analyst will work closely with finance teams, IT, and control functions to troubleshoot data quality issues, assist in root cause analysis, and implement defined solutions.

Staff supervision/ Organizational Structure

The Analyst will report to the Head of Data Integrity and Control and will work within a global team environment.

Work conditions

This position provides for standard working conditions in an office and a normal work schedule from Monday to Friday. This position requires little travel.

Key Responsibilities

Data Quality Rule Implementation (DQR)

• Develop, test, and deploy Data Quality Rules (DQRs) using SQL to ensure data accuracy, completeness, and consistency.
• Translate business requirements into technical SQL logic for validation and implementation.
• Collaborate with finance teams to identify and address data quality issues raised in operational or regulatory contexts.
• Assist in troubleshooting data quality gaps and supporting the implementation of sustainable solutions.

Data Quality Monitoring & Reporting

• Support the maintenance of data quality dashboards (e.g., Power BI, Tableau) to track KPIs (e.g., accuracy, completeness, timeliness).
• Generate regular status reports highlighting data inconsistencies and anomalies for stakeholders.
• Assist in monitoring alerts for SLA breaches and producing performance reports for management.

Process Support & Documentation

• Assist in identifying opportunities to automate workflows and enhance data quality processes.
• Maintain clear and up-to-date documentation for DQRs, SQL scripts, and business requirement translations.
• Contribute to knowledge sharing to ensure team alignment on data quality standards.

Collaboration & Stakeholder Engagement

• Work alongside IT, business lines, and control functions to support the integration of DQRs across platforms.
• Support data integration projects by validating data fitness for reporting.
• Assist in implementing mitigation plans for identified data-related risks.

The strengths and skills that will help you succeed

Education

• Bachelor’s degree in computer science, Information Management, Data Science, Business Administration, Finance, or a related field.

Years of Experience

• 4–6 years of professional experience in:
• SQL development (writing queries, testing, and rule implementation).
• Data quality support (assisting in DQR creation and validation).
• Business analysis (translating requirements into technical logic).
• Working within financial data environments.

Languages

• English (mandatory).
• French (a plus).

Technical Skills

• SQL: Strong proficiency in query development and data manipulation.
• Data Quality Tools: Experience with data validation frameworks or metadata management tools (e.g., Collibra) is an asset.
• Visualization Tools: Familiarity with Power BI or Tableau for dashboarding.
• Project Management Tools: Experience with Jira or Azure DevOps.
• Client Office Suite: Proficiency in Excel (for analysis) and Word/PowerPoint (for documentation).

Soft Skills

• Technical Communication: Ability to translate business needs into technical steps and communicate with both technical and non-technical colleagues.
• Problem-Solving: Analytical mindset to troubleshoot data discrepancies and identify causes.
• Collaboration: Ability to work effectively within a global, multi-functional team.
• Rigour: High attention to detail and a commitment to data accuracy.
• Adaptability: Ability to manage tasks in a fast-paced, regulatory-driven environment.