Production Support Engineer Jobs in Quebec (NOW HIRING)

We are looking for an experienced data developer to support a new analytics platform in production and contribute to its upcoming release within a large financial services organization. The solution integrates data from multiple systems in an Azure cloud environment and makes it available through a data warehouse using Power BI. The project is progressing in iterations, each delivering value to users, until the planned handover to the operations team in summer 2027. You will be central to the stability and evolution of the solution: providing technical support after production releases, monitoring the platform, resolving issues with the team, developing ETL processes, and configuring data ingestion pipelines from source systems to data lakes. You will participate in data valuation and the configuration of the data warehouse according to the established model, perform unit testing, and document the processes.
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The client is seeking a data developer with 8+ years of experience to initially provide production support for the Group Insurance Data Hub, while continuing to contribute to Release 2. The core of the role is data engineering on the Azure stack: data ingestion into data lakes, dimensional modeling (dimensions and facts), and data exposure using Power BI. The recurring keywords (ETL, ingestion pipelines, Data Factory, Synapse, unit testing, continuous integration) indicate that the ideal candidate will write and debug processing code, not be a Power BI report writer or functional analyst. The production support context requires someone capable of independently diagnosing and resolving anomalies within a standardized process environment. This is neither an architect nor a project management role; therefore, candidates with primarily strategic or decision\-making experience should be excluded.<\/span>
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Responsibilities :
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• Provide technical support to operations following production deployments and follow up on issues with project managers. <\/span>
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• Perform solution monitoring activities. <\/span>
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• Take responsibility for resolving solution anomalies, in collaboration with other members of the project team. <\/span>
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• Analyze system components, functional and non\-functional specifications, change requests, and any technical issues encountered. <\/span>
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• ETL Analysis and Development Configuration of data ingestion pipelines from source systems to appropriate data lakes Participation in data enhancement and data warehouse configuration (dimension\/fact configuration) according to the established data model Participation in data loading into tables Process breakdown and documentation Data profiling (tools, approaches) <\/span>
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• Performing unit testing Participating in production deployments Ensuring and performing updates to various databases and recommending any improvements aimed at optimizing their quality and efficiency.
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  Requirements<\/h3>

  REQUIREMENTS
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  • 8+ years of hands\-on experience as a developer in a large enterprise | Required | All requirements met<\/span>
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  • Excellent ETL knowledge and ETL development skills | Required | All requirements met<\/span>
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  • Source system to data lake ingestion pipelines | Required | All requirements met<\/span>
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  • Relational and dimensional models, dimension and fact configuration | Required | All requirements met<\/span>
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  • Azure data storage (Data Lake, Blob Storage, Data Factory, Azure SQL Database, Synapse Analytics) | List of examples | Sufficient majority<\/span>
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  • Power BI (Desktop, Service, components including gateway) | Required | All requirements met<\/span>
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  • Unit testing approaches (TDD), automated testing, and continuous integration | List of examples | Sufficient majority<\/span>
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    DESIRED<\/span>
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    • Source code management and deployment (GitHub, GitHub Actions, Concourse) | List of examples | Sufficient majority<\/span>
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    • Experience in data projects | Required | All requirements met<\/span>
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    • Architecture patterns (Object\-Oriented, Cloud IaaS, CaaS, PaaS, SaaS, iPaaS) | List of examples | Sufficient majority<\/span>
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      ASSET<\/span>
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      • Domain\-Driven Design (DDD) | Required | Sufficient majority<\/span>
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      • Application resilience and event\-driven architecture | List of examples | Sufficient majority<\/span>
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      • Security principles and protocols (SSO, Auth0, SAML, OpenID, JWT, OAuth2, ABAC, RBAC) | List of examples | Sufficient Majority<\/span>
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      • Note: The Azure stack is listed as an ecosystem; proficiency in most components with concrete projects is considered comprehensive. The absence of a single service does not disqualify you.<\/span>
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        WHAT WE DON'T WANT<\/span>
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        • Profiles of Power BI report writers without real experience in ETL development and data ingestion.<\/span>
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        • Profiles of functional or BI analysts without experience writing data processing code.<\/span>
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        • Profiles of architects or managers whose recent experience is in business intelligence rather than hands\-on development.<\/span>
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        • Profiles of data engineers outside of Azure without demonstrated transferability to Data Factory and Synapse.<\/span>
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        • Profiles of junior or intermediate profiles with less than 8 years of development experience in large companies.<\/span>
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        • Profiles incapable of working independently in production support and accustomed to close supervision.<\/span>
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