Publié il y a 8 jours
Finance Business & Data Analyst
@ eTeam
Montréal, Québec
SIGNAUX
Résumé des exigences :
- This role ensures service continuity by assisting in the deployment of rules, maintaining documentation, and translating business requirements into technical logic.
- Translate business requirements into technical SQL logic for validation and implementation.
- 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.
- Bachelor’s degree in computer science, Information Management, Data Science, Business Administration, Finance, or a related field.
- Years of Experience
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-11-02
- Première détection par notre source
- 2026-11-10
- Mise à jour du dossier source
- 2026-11-10
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
eTeam
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 7 |
Description
Job title:- Finance Business & Data Analyst
Location:- Montreal
Duration:- 12 Months
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 willworkwithin a global teamenvironment.
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.
- 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.
- 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.
- 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.
Education
- Bachelor’s degree in computer science, Information Management, Data Science, Business Administration, Finance, or a related field.
- 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.
- English (mandatory).
- French (a plus).
- 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.
- Microsoft Office Suite: Proficiency in Excel (for analysis) and Word/PowerPoint (for documentation).
- 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.
Journal
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