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
- 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
- Microsoft Fabric, Azure Data Factory, Azure Functions, Dataflows
- Experience in an Azure/Microsoft setting
- Power BI exposure

Disclaimer:

AI may be used in evaluating candidates.

This posting is for an existing vacancy.

#J-18808-Ljbffr

📌 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… (Montreal)
🏢 S.I. Systems
📍 Montreal