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Data Engineer Architect Jobs in Quebec (NOW HIRING)

Maarut

This is neither an architect nor a project management role; therefore, candidates with primarily ... Profiles of data engineers outside of Azure without demonstrated transferability to Data Factory ...

Global Excel Management

Data Developer II

Sherbrooke, QC · On-site

CA$35.06 - CA$46/hr

As a Data Developer II, you will be responsible for designing, implementing, and maintaining GEM ... Architect data solutions leveraging DBT for data transformation and Azure Data Factory for pipeline ...

Global Excel Management

Data Developer II

Sherbrooke, QC

CA$35.06 - CA$46/hr

As a Data Developer II, you will be responsible for designing, implementing, and maintaining GEM ... Architect data solutions leveraging DBT for data transformation and Azure Data Factory for pipeline ...

Cogeco

Specialist, Data Engineering

Montreal, QC · On-site

Reporting to the Lead Data Engineering, the Data Engineering Specialist is responsible for ... Collaborate with Data Analysts and Data Architects on defining data models, requirements, and ...

2K

Senior Data Developer

Montreal, QC

Senior Data Developer Who We Are 2K is headquartered in Novato, California and is a wholly owned ... What You Will Do Architect and automate scalable ETL pipelines to ingest and centralize diverse ...

Medfar

Senior Data Transfer Developer

Montreal, QC · On-site +1

As a Senior Data Transfer Developer, you will design, build, and evolve robust data transfer ... Define the architecture and evolution strategy for data transfer tools and integration platforms

Xideral

Minimum de 5 ans d'expérience comme Ingénieur de données * Expérience dans des organisations de ... Data Vault, Event-Driven Architecture ou Self-Service Analytics * Expérience dans des ...

Transat AT

Architecte de données

Montreal, QC · On-site

Définir, documenter et faire évoluer les architectures de données (Data Warehouse, Data Lake ... Promouvoir l'adoption des pratiques DataOps, DevOps et CI/CD, incluant l'automatisation des tests ...

KPMG

Security Architect

Brossard, QC · On-site

The Security Architect will work with Business groups, Architects, Developers and other team ... data protection * Analyzing requirements for cloud security tools and technology and support ...

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Data Engineer Architect information

What are the key skills and qualifications needed to thrive as a data engineer architect, and why are they important?

To thrive as a Data Engineer Architect, you need expertise in data modeling, ETL processes, big data platforms, and a strong background in computer science or a related field. Proficiency with tools and systems such as Hadoop, Spark, SQL/NoSQL databases, and cloud platforms like AWS or Azure, along with relevant certifications, is highly valued. Strong problem-solving, communication, and project management skills distinguish top performers in this role. These capabilities are crucial for designing scalable, reliable data architectures that support business analytics and decision-making.

What is the difference between Data Engineer Architect vs Data Engineer?

AspectData Engineer ArchitectData Engineer
CredentialsBachelor's/Master's in CS, certifications like AWS, GCP, or AzureBachelor's in CS, certifications like AWS, GCP, or Azure
Work EnvironmentDesigns data infrastructure, collaborates with architects and stakeholdersBuilds and maintains data pipelines, works with data storage and processing
Employer & Industry UsageUsed in organizations with complex data architecture needsCommon across industries for data processing tasks

The main difference is that Data Engineer Architects focus on designing and planning the overall data infrastructure, while Data Engineers implement and maintain the pipelines and systems. Architects have a broader strategic role, whereas Engineers focus on execution and operational tasks.

How does a data engineer architect typically collaborate with data scientists and business analysts on large-scale projects?

A Data Engineer Architect plays a pivotal role in facilitating collaboration between data scientists, business analysts, and other stakeholders by designing robust data pipelines and scalable architectures that ensure reliable, timely access to data. They often gather requirements, translate business needs into technical solutions, and oversee the integration of diverse data sources. Regular communication and joint planning sessions help align the data infrastructure with analytical goals, making teamwork and cross-functional coordination essential aspects of the role. This collaborative environment fosters innovative problem-solving and ensures that the data architecture supports both immediate project needs and long-term business objectives.

What is a data engineer architect?

A Data Engineer Architect is a professional responsible for designing, building, and maintaining the architecture that allows organizations to collect, store, process, and analyze large volumes of data. They create scalable and reliable data pipelines, choose appropriate technologies, and ensure that data systems meet business requirements for performance and security. Data Engineer Architects often collaborate with data scientists, analysts, and other engineers to optimize data workflows and support decision-making processes. Their expertise is crucial for organizations looking to leverage big data and advanced analytics.
Data Engineer Architect jobs near you

Senior Data Developer

Maarut

On-site

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

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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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