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Added 6 mins ago
CO
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SapienX Inc.

Contract Data Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Contract

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Job details

Job type: Contract
Apply by: May 3, 2027
Posting language: English
Posted: Nov 4, 2026

Original job description

SapienX, Inc. is looking for an experienced Data Engineer for a 6-month consulting engagement supporting our clients.

We’re looking for someone who can hit the ground running in an established enterprise data environment and contribute immediately across both day-to-day platform needs and ongoing enhancements.

This isn't a role where you'll spend your first few months designing something that may eventually go into production. You'll be working with real enterprise data pipelines and production workloads, solving problems, improving reliability, and helping an experienced data engineering team continue evolving the platform.

What you'll be working with

You'll want to be very comfortable with:

Azure Data Factory
Azure Databricks and Lakehouse architectures
PySpark and Python
Azure Logic Apps
SQL and complex data transformations
Production support, troubleshooting, monitoring, and incident resolution
CI/CD and structured DEV → QA → PROD deployment practices

Our architecture is moving toward a governed medallion model spanning SAP Business Data Cloud/Datasphere, Azure Databricks and ADLS, Microsoft Fabric/OneLake, Unity Catalog, and Power BI, so experience working across modern enterprise lakehouse patterns would be particularly relevant.

Who we're looking for

This opportunity is especially well suited to a mid-to-senior or senior Data Engineer who:

Enjoys getting hands-on with real production data problems
Can troubleshoot an unfamiliar pipeline and systematically get to root cause
Is comfortable both supporting what exists and improving it
Writes clean, maintainable Python/PySpark and SQL
Understands how enterprise data solutions move safely through development, QA, and production
Works collaboratively and communicates clearly with other engineers and stakeholders
Can operate effectively without needing extensive ramp-up or day-to-day direction

Even better if you know

Experience in any of these areas would be a strong plus:

SAP data integration
SAP Business Data Cloud (BDC)
SAP Datasphere
Microsoft Fabric
Power BI data models
Unity Catalog
Azure SQL / Cosmos DB
Modern medallion/lakehouse architecture

Engagement

Duration: 6 months

Engagement: Contract through SapienX, Inc.

Focus: Azure data engineering, production support, pipeline enhancements, and platform evolution

If you're the kind of engineer who enjoys opening a failing pipeline, figuring out why it failed, fixing it properly, and then asking "how do we make sure this doesn't happen again?", I'd especially like to hear from you.

Interested? Send me a message on LinkedIn with a short introduction and your resume.

#DataEngineering #Azure #Databricks #PySpark #Python #AzureDataFactory #SQL #MicrosoftFabric #Lakehouse #SAP #ContractJobs

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More about this job

Responsibilities

Support and troubleshoot production data pipelines and workloads, resolve incidents, and improve platform reliability. Enhance and evolve the enterprise data platform across Azure, Databricks, SAP, Microsoft Fabric, and related lakehouse technologies.

Requirements

The role calls for a mid-to-senior or senior Data Engineer with strong hands-on experience in Azure Data Factory, Databricks, PySpark, Python, SQL, production support, and CI/CD deployment practices. Candidates should be able to diagnose unfamiliar pipelines, work effectively with limited ramp-up, and communicate collaboratively; SAP, Fabric, Power BI, Unity Catalog, and modern lakehouse experience are advantageous.

Skills

Azure Data Factory
Azure Databricks
Lakehouse Architecture
PySpark
Python
Azure Logic Apps
SQL
Complex Data Transformations
Production Support
Troubleshooting
Monitoring
Incident Resolution
CI/CD
SAP Data Integration
Microsoft Fabric
Unity Catalog

Visa sponsorship

Not detected in the job text

Keywords

Azure Data Factory
Azure Databricks
Lakehouse Architecture
PySpark
Python
Azure Logic Apps
SQL
Complex Data Transformations
Production Support
Troubleshooting
Monitoring
Incident Resolution
CI/CD
DEV-QA-PROD Deployment
SAP Data Integration
SAP Business Data Cloud
SAP Datasphere
Microsoft Fabric
OneLake
Unity Catalog
Power BI
ADLS
Azure SQL
Cosmos DB
Medallion Architecture
Enterprise Data Pipelines
Data Engineering
Platform Evolution

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