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.

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