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Desjardins is seeking a senior data valorization advisor to design and implement Power BI dashboards, perform advanced analytics, and guide data governance initiatives. The role focuses on strengthening governance for non-financial risk data across IT and business teams.
The position requires a bachelor’s degree, at least six years of relevant experience, fluency in French, and strong skills in SQL, DAX, Power BI, Excel, and Power Automate.
The Guidance and Support Strategy Administrative Department’s mandate is to improve coordination of the Risk Management Executive Division's work with the first line of defence and drive innovation in tools, information analytics and data for the Non-Financial Risks, Chief Risk Officer, Technology and Cyber Risk Division. As a senior data valorization advisor, you help develop and use methods and tools to collect, consolidate, model and present material and immaterial information to establish governance, support decision-making and give decision-makers a comprehensive view of the activity in question. You provide specialist expertise for practitioners on matters and projects involving non-financial risk management and innovative strategic initiatives. Your initiatives require extensive, in-depth knowledge of your specialty area. Interpersonal savvy is therefore essential.
Temporary 12-month position
At Desjardins, we believe in equity, diversity and inclusion. We're committed to welcoming, respecting and valuing people for who they are as individuals, learning from their differences, embracing their uniqueness, and providing a positive workplace for all. At Desjardins, we have zero tolerance for discrimination of any kind. We believe our teams should reflect the diversity of the members, clients and communities we serve.
If there's something we can do to help make the recruitment process or the job you're applying for more accessible, let us know. We can provide accommodations at any stage in the recruitment process. Just ask!
Action oriented, Business insight, Complexity, Customer Focus, Differences, Nimble learning
Data (FG)