Contract Data Engineer
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- Posting language
- English
- Posted
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 withYou'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 forThis 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
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
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
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
Categories
- Data & Analytics
- Technology
- Software
- Engineering
- Consulting
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