Intermediate to Senior Data Engineer to build scalable Databricks pipelines (PySpark, SQL, medallion architecture) on Azure, enabling automated, self service Power BI reporting for a leading North American utility’s data and analytics transformation. Intermediate to Senior Data Engineer (Databricks)
6 month contract, likely extension | Remote, Canada (EST hours) | 40 hrs/week
About the Project
Our client, a leading North American utility, is transforming its data and analytics function. The team is moving away from ad hoc, ticket based reporting toward a scalable data platform that delivers automated, self service reporting in Power BI. You’ll help build out close to 100 business metrics across a layered (medallion) architecture in Databricks, with more to follow as the platform grows. The team recently adopted Agile with 2 week sprints.
Responsibilities
Design, build, and maintain data pipelines in Databricks using PySpark and SQL
Develop and organize data across bronze, silver, and gold layers (medallion architecture)
Translate business requirements into reliable, reusable data models and metrics
Enable automated reporting and self service analytics in Power BI
Ingest and integrate data from multiple sources, including SAP and Azure services
Improve data quality, performance, and pipeline reliability
Work within Agile sprints alongside data architects, analysts, and business partners
Must Haves
5 to 10+ years of data engineering experience
Strong hands on experience with Databricks
PySpark and Databricks SQL
Medallion architecture experience
Nice to Haves
Utility industry experience (billing, accounts receivable, customer operations, call centre, outage management, ADMS, or meter/premise data)
SAP data experience (functional or technical)
Python




Experience in an Azure/Microsoft environment
Intermediate to Senior Data Engineer (Databricks)
6 month contract, likely extension | Remote, Canada (EST hours) | 40 hrs/week
About the Project
Our client, a leading North American utility, is transforming its data and analytics function. The team is moving away from ad hoc, ticket based reporting toward a scalable data platform that delivers automated, self service reporting in Power BI. You’ll help build out close to 100 business metrics across a layered (medallion) architecture in Databricks, with more to follow as the platform grows. The team recently adopted Agile with 2 week sprints.
Responsibilities
Design, build, and maintain data pipelines in Databricks using PySpark and SQL
Develop and organize data across bronze, silver, and gold layers (medallion architecture)
Translate business requirements into reliable, reusable data models and metrics
Enable automated reporting and self service analytics in Power BI
Ingest and integrate data from multiple sources, including SAP and Azure services
Improve data quality, performance, and pipeline reliability
Work within Agile sprints alongside data architects, analysts, and business partners
Must Haves
5 to 10+ years of data engineering experience
Robust hands on experience with Databricks
PySpark and Databricks SQL
Medallion architecture experience
Nice to Haves
Utility industry experience (billing, accounts receivable, customer operations, call centre, outage management, ADMS, or meter/premise data)
SAP data experience (functional or technical)
Python
Microsoft Fabric, Azure Data Factory, Azure Functions, Dataflows
Experience in an Azure/Microsoft environment
Power BI exposure
Disclaimer:
AI may be used in evaluating candidates.
This posting is for an existing vacancy.

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📌 Intermediate to Senior Data Engineer to build scalable Databricks pipelines (PySpark, SQL, medallion (Ontario)
🏢 S.I. Systems
📍 Ontario