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Data Engineering Azure Cloud Computing: Infrastructure & Operations Data Warehousing

Data Platform Engineer to build and manage Microsoft Fabric and Azure- data platforms

Job in Toronto, Ontario, M5A, Canada
Listing for: S.i. Systems
Contract position
Listed on 2026-07-21
Job specializations:
  • IT/Tech
    Data Engineering, Azure, Cloud Computing: Infrastructure & Operations, Data Warehousing
Job Description & How to Apply Below
Position: Data Platform Engineer to build and manage Microsoft Fabric and Azure-based data platforms

Our financial services client is seeking a Senior Data Platform Engineer (10+ years) to build and manage Microsoft Fabric and Azure-based data platforms

Join a data analytics team delivering enterprise-scale platform engineering initiatives within a financial services environment. This role focuses on Microsoft Fabric, Azure Data Factory, Synapse, ADLS, Snowflake, and Databricks to support modern data integration and lakehouse architectures. The position requires hands-on delivery of automated, reusable technical patterns across cloud-based data platforms. Prior financial services exposure within capital markets, private markets, or pensions is considered a strong asset.

Must Haves

  • 10+ years in platform engineering
    , cloud architecture
    , or data engineering
  • Hands-on expertise with Microsoft Fabric
    , Azure Data Factory
    , Synapse
    , and ADLS for data integration pipelines
  • Enterprise-scale administration of Snowflake including Snowpark
    , data sharing
    , and performance tuning
  • Hands-on delivery using Databricks
    , lakehouse architectures
    , MLflow
    , Terraform
    , Azure Dev Ops
    , and Git Hub Actions
  • Degree in a related technical field

    • Nice to Have

  • Financial services experience within capital markets, private markets, or pensions
  • Exposure to Prefect or Airflow
  • Hands-on work with dbt and dimensional modeling

    • Responsibilities

  • Configure, deploy, and manage Snowflake environments at enterprise scale
  • Build and manage data integration pipelines within the Azure data ecosystem
  • Set up and support unified lakehouse architectures and MLflow environments in Databricks
  • Implement infrastructure-as-code and CI/CD processes tailored to data platforms
  • Implement cross-platform observability and workflow orchestration solutions
  • Develop automated and reusable technical patterns for cloud data platforms
  • Document technical processes and collaborate with engineering and strategic teams
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