Senior Data Engineer / Azure Data Factory Developer
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
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- Posting language
- English
- Posted
Original job description
Our client is seeking two Senior Data professionals to support a data engineering and integration initiative: one Data Engineer specializing in Databricks and Apache Spark, and one Azure Data Factory Developer focused on ETL and data integration. The engagement will include one onsite/hybrid resource in Toronto and one offshore resource, with both resources required to complete onboarding before the end of October 2026.
Role 1: Senior Data Engineer, Databricks / Apache Spark
Delivery Model: This role may be filled by either the onsite/hybrid Toronto resource or the offshore resource. Across the two positions, one resource will be onsite and one offshore.
Responsibilities
- Design, develop and maintain data processing solutions using Databricks
- Develop and optimize Apache Spark jobs for data transformation and processing
- Build data ingestion and transformation workflows
- Develop scalable, reusable and unit-tested data engineering components
- Troubleshoot Databricks and Spark workloads
- Support deployment, issue resolution and enhancement activities
- Produce technical documentation and support knowledge transfer
Required Skills
- Strong Databricks experience
- Strong Apache Spark experience
- Data transformation and processing
- Data ingestion and pipeline development
Role 2: Senior Azure Data Factory Developer
Delivery Model: This role may be filled by either the onsite/hybrid Toronto resource or the offshore resource. Across the two positions, one resource will be onsite and one offshore.
Responsibilities
- Design, build and maintain Azure Data Factory pipelines and workflows
- Develop ETL and data integration solutions across source and target systems
- Support integrated processing and orchestration using Databricks where required
- Configure pipeline monitoring and error handling
- Troubleshoot and optimize data movement and pipeline execution
- Support testing, deployment and operational stabilization
- Produce technical documentation and support knowledge transfer
Required Skills
- Strong Azure Data Factory experience
- Working knowledge of Databricks
- Data integration experience
- ETL pipeline development and support
More about this job
Responsibilities
The Databricks engineer will build and tune data pipelines and transformations. The Azure Data Factory developer will build and maintain ETL pipelines and data movement between systems.
Requirements
Candidates need strong hands-on experience with Databricks and Apache Spark, or with Azure Data Factory and ETL integration. Working knowledge of the other platform is also needed.
Skills
- Databricks
- Apache Spark
- Azure Data Factory
- ETL pipeline development
- Data ingestion
- Data transformation
- Data integration
- Pipeline orchestration
- Pipeline monitoring and error handling
- Troubleshooting Spark workloads
- Technical documentation
- Unit testing data components
Categories
- Technology
- Data & Analytics
- Software
- Consulting
Keywords
- Databricks
- Apache Spark
- Azure Data Factory
- ADF
- ETL
- data engineering
- data integration
- data pipelines
- data ingestion
- data transformation
- Azure
- PySpark
- orchestration
- data warehousing
- contract
- senior data engineer
- hybrid
- offshore
Seniority
Senior
Tools
- Databricks
- Apache Spark
- Azure Data Factory
Languages
- English