Test Engineer (Data)
- Toronto, ON, Canada
$105,000 to $135,000 CAD / year · Full-time
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Job details
- Pay
- $105,000 to $135,000 CAD / year
- Job type
- Full-time
- Apply by
- Experience
- 2+ years hands-on experience with Databricks (Spark)
- Posting language
- English
- Posted
Original job description
Test Engineer (Data)
Job Type: Permanent
Pay Rate/Salary: CAD $105,000 to CAD $135,000
Location: Hybrid: 3 days per week on-site Toronto
Your New Role
As a Test Engineer - Data, you will be responsible for developing and implementing automated testing frameworks for Databricks-based solutions, data pipelines, and data quality validation. You will work closely with data engineering teams to ensure data accuracy and reliability across our Lakehouse architecture.
What You Need to Do
- Data Pipeline Testing
- Automate testing for ETL/ELT processes in Databricks
- Implement Spark job testing and optimization validation
- Create test cases for data ingestion and processing workflows
- Develop automated checks for data transformations
- Test Unity Catalog features and access controls
- Databricks Testing
- Design and implement automated testing for Databricks notebooks and workflows
- Create test frameworks for Delta Lake tables and ACID transactions
- Develop automated validation for structured streaming pipelines
- Validate Delta Live Tables implementations
- Quality Assurance
- Design and execute data quality test strategies
- Implement automated data reconciliation processes
- Develop performance testing for large-scale Spark jobs
- Monitoring & Reporting
- Implement pipeline monitoring test frameworks
- Create automated test dashboards
- Generate quality metrics and testing reports
- Maintain comprehensive test documentation
What You'll Need to Succeed:
- Educational Background
- Bachelor’s degree in Computer Science, Data Science, or related field
- Relevant certifications in Databricks or data testing are a plus
- Technical Experience
- 2+ years hands-on experience with Databricks (Spark)
- Strong programming skills in Python (PySpark) and SQL
- Experience with data testing frameworks and tools
- Proficiency with AI coding agents such as Claude Code, Cursor, Kiro
- Knowledge of AWS services (S3, Glue, Lambda)
- Understanding of Delta Lake and Lakehouse architecture
- Experience with version control systems (Git)
- Additional Skills
- Strong analytical and problem-solving abilities
- Experience with large-scale data processing
- Knowledge of data quality best practices
- Understanding of data governance and compliance requirements
- Experience with Agile methodologies
- Platform Knowledge
- Databricks workspace and notebook development
- Delta Lake and Delta Live Tables
- Unity Catalog for governance testing
- Spark optimization and performance testing
What You'll Get in Return:
You will have the opportunity to work with a talented team of professionals in a dynamic and supportive environment. Client is offering competitive compensation, professional development opportunities, and the chance to make a significant impact on our clients' success.
What You Need to Do Now:
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion on your career.
This posting is for an existing vacancy with the organization.
AI may be used to screen, assess or select applicants for the position.
#1126958 - Shivangi Gupta
More about this job
Responsibilities
The Test Engineer will build automated tests for data pipelines and Databricks workflows, check data quality and accuracy, and report test results and metrics. The role works closely with data engineering teams.
Requirements
Candidates need 2+ years of hands-on Databricks and Spark experience, strong Python (PySpark) and SQL skills, and knowledge of Delta Lake, AWS and Git. A bachelor's degree in a related field is required; Databricks or data testing certifications are a plus.
Skills
- Databricks
- Apache Spark
- PySpark
- Python
- SQL
- Delta Lake
- Delta Live Tables
- Unity Catalog
- Structured Streaming
- AWS S3
- AWS Glue
- AWS Lambda
- Git
- Test automation frameworks
- Data quality validation
- Data reconciliation
- ETL/ELT testing
- Spark performance testing
- Data governance
- Agile methodologies
- AI coding agents (Claude Code, Cursor, Kiro)
Benefits
- Professional development opportunities
Categories
- Technology
- Data & Analytics
- Software
Keywords
- Databricks
- Spark
- PySpark
- Python
- SQL
- Delta Lake
- Delta Live Tables
- Unity Catalog
- Structured Streaming
- AWS
- S3
- Glue
- Lambda
- Git
- ETL
- ELT
- Data quality testing
- Data reconciliation
- Lakehouse
- Agile
Seniority
Mid level
Tools
- Databricks
- PySpark
- Delta Lake
- Unity Catalog
- AWS S3
- AWS Glue
- AWS Lambda
- Git
- Claude Code
Languages
- English
Fields of study
- Computer Science
- Data Science