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Data Architect

Data Architect

CGIOntario, Canada
28 days ago
Job description

Data Architect

Are you a Data Architect or a Senior Data Engineer interested in working in a talented and collaborative team developing Cloud, Data and AI solutions for leading global clients? Do you regularly find yourself in conversations on disparate and dispersed data sources and feel the need to create a robust data engineering infrastructure to sort that mess out? If you have that hands-on technical expertise of enabling data engineering, designing data architectures, a genuine flair for solving data problems, and the mindset to collaborate with diverse clients and team members alike, we're looking for you.

  • This is a hands-on architect role with responsibility to lead teams of technical members

Location : This role is flexible within proximity to a CGI office to support a hybrid working model.

The Emerging Technologies team in Global Technology and Operations (GTO) Canada at CGI is a trusted Data, Cloud and Advanced Analytics advisor and go-to implementation partner for our global clients data needs. We're an entrepreneurial team that is on a continuous mission to position CGI as the best-in-class Cloud and Data partner and develop new and exciting opportunities in latest technologies. In our endeavor to provide end-to-end Cloud and Machine Learning capabilities, we start with learning about the clients` business and data landscape, assess possible opportunities, help shortlist and turn those opportunities into action, and then scale it across the organization unlocking a larger impact for clients and their consumers. For this, we depend on a talented and motivated team of Data Architects, Data Scientists, Data Engineers, Cloud DevOps professionals, Cloud Architects and other solutions experts.

As a Data Architect / Senior Data Engineer on this team your main responsibilities will include :

  • Working HANDS-ON on client engagements and managing E2E client engagements as the Senior Data Architect and Tech Lead
  • Creating data architectures, data pipelines, and data flows for requirement at hand
  • Delivering on areas of data preparation and transformations and ETL or ELT development on Azure - Azure Data Factory (ADF), Synapse, Azure Databricks, Azure Data Lake (ADLS), Azure SQL database, Azure SQL Datawarehouse or AWS / GCP equivalents
  • Creating client proposals for ML / AI and Data projects
  • Mentoring junior Data Engineers, Data Scientists and Data professionals in the team
  • Thought leadership amongst clients and the industry

    • Other responsibilities :

  • Strategically collaborating with the clients to explore and deliver key foundational data-driven solutions
  • Delivering on areas of data preparation and transformations and ETL or ELT development both on-prem or on-cloud
  • Building Data Engineering pipelines on cloud (Azure, AWS, GCP and others)
  • Working in a business environment with large-scale, complex and big data datasets and dispersed data sources
  • Using Advanced SQL and Python skills as necessary
  • Gathering client requirements, coding and implementing data solutions while leading a small team
  • Implementing proof of concepts to show value and then package and scale to full data engineering scale on both on-prem and cloud environments

    • Essential Qualifications

  • 6+ years relevant hands-on experience in Data Architecture, Data Engineering or Data Science with 9+ years of overall experience
  • Experience consulting clients or stakeholders on Data and AI engagements
  • Hands-on experience with latest tools and at least one modern cloud platform (Azure, AWS, GCP etc.)
  • Data analysis, storage, data pipelines, and orchestration
  • Expert Python and SQL skills
  • Experience working on Big Data
  • Excellent communication and team working skills
  • English language is mandatory; French language is nice to have

    • Nice to Have Qualifications

  • Consulting background is an asset
  • Experience with building client proposals and sales enablement is an asset
  • Experience with ML projects is an asset
  • Experience with data pipeline and workflow management tools eg. Airflow, Jenkins etc.
  • Experience in a variety of tools like Azure Data Factory, Google Dataflow, Qlik Compose, AWS Data Pipeline or Glue, Talend, Microsoft SSIS, IBM Datastage, Informatica