Data Architect

Here's a brief overview of the tasks and responsibilities you'll have :
• Support data-related dimensions of solutions, including flows, authoritative sources, analysis, profiling, integration, modeling, optimization, data management, and exposure;
• Determine the most appropriate data integration and exposure approaches for the investment industry, taking into account the needs of the context and the sustainability of the solutions;
• Participate in the governance of data-related processes, particularly with regard to data quality;
• Align solutions with functional and non-functional requirements, including volumes, refresh rate, and long-term data growth;
• Ensure compliance of data solutions with enterprise data integration models;
• Document data solutions and maintain associated artifacts, including feeds, data models, message models, and value domains, while contributing to data innovation;
• Integrate the possibilities offered by artificial intelligence, including generative artificial intelligence, into the design of data architectures in order to improve the exploitation, valorization and automation of data;
• Collaborate with stakeholders to oversee the safe and responsible use of artificial intelligence in data solutions, particularly in terms of data governance, quality, traceability and protection;
• Evaluate use cases for artificial intelligence applied to data, including augmented search, classification, enrichment, automated analysis, and decision support, based on their business value and technological feasibility;
• Support the design and production of physical data structures.


The profile we are looking for is as follows:
• Hold a bachelor's degree in a related field and at least 8 years of relevant experience;
• Possess expertise primarily focused on data architecture, complemented by expertise in solution architecture to design solutions that are coherent, integrated, and aligned with the overall architecture of systems;
• Experience in conceptual, logical, and physical data modeling in transactional and informational contexts;
• Master artificial intelligence concepts and technologies applied to systems architecture, including generative artificial intelligence, language models, augmented search, vectorization, and vector databases;
• Know the risks associated with artificial intelligence as well as the appropriate mitigation mechanisms;
• Understand the concepts of master data, master data, authoritative sources, domain-driven design (DDD), data governance, enterprise data catalog, data security, and access management;
• Proficient in data integration and leverage approaches, including APIs, streaming, ETL processes, business intelligence, analytics, data warehouses, and data virtualization;
• Demonstrate excellent ability to analyze flows and impacts between systems;
• Possess a strong ability to synthesize, analyze and popularize as well as an ability to effectively lead workshops and meetings;
• Demonstrate the ability to work in a team and under pressure, as well as authenticity and leadership in service of others;
• Hold a certification in data management, including the Data Management Professional certification (an asset);
• Knowledge of the investment industry (an asset);
• Experience with agile methodologies (an asset).