Senior Data Integration Specialist
Design and build Silver-to-Gold Databricks pipelines to enable data flow between insurance platforms and analytics solutions. Develop complex transformations and optimize Spark workloads for performance and scalability.
- Remote
- Canada
- Posted Aug 5, 2026
- Apply by Sep 4, 2026
- 1 position
Job summary
Role: Senior Data Integration Specialist Pay Range: $62-64/hour Contract: 14 months Location: Remote across Canada or 2x/week on site at any Co-op office - Guelph, Toronto, Mississauga, Burlington, Quebec City, MTL, Calgary, Regina A leading Canadian insurance company is seeking a Senior Data Integration Specialist to support a major data modernization initiative focused on enabling data flow between core insurance platforms and downstream pricing, rating, and analytics solutions. Responsibilities: Design and build Silver-to-Gold Databricks pipelines Develop complex transformations using PySpark, Python, and SQL Build curated datasets and data products for analytics and business teams Perform data validation, reconciliation, and root cause analysis Troubleshoot data quality and integration issues Optimize Databricks and Spark workloads for performance and scalability Must Haves: 5+ years of experience of hands-on data engineering and development Designing and implementing silver-to-gold pipelines in Databricks Developing complex business transformations using PySpark, Python, and SQL Experience validating the data - building metrics, how to approach reconciliation, etc. We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position. Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.
What you’ll do
Design and build Silver-to-Gold Databricks pipelines to enable data flow between insurance platforms and analytics solutions. Develop complex transformations and optimize Spark workloads for performance and scalability.
Requirements
Requires over 5 years of hands-on data engineering experience with a focus on Databricks, PySpark, Python, and SQL. Must have proven expertise in implementing data pipelines and performing data reconciliation and validation.
Listed skills
- SQLPreferred
- PythonPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data Engineering
- Databricks
- PySpark
- Python
- SQL
- Data Integration
- Data Validation
- Data Reconciliation
- Performance Optimization
- Silver-to-Gold Pipelines
Job areas
- Data & Analytics
- Technology
- Software
- Consulting
- Engineering
Additional details
- Minimum experience
- 5+ years
- Apply by
- Sep 4, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Guelph, Ontario, Canada
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available