Data Quality Engineer (Intermediate) remote contract
- Canada
- Remote
- Posted Sep 19, 2026
- 1 position
$65–$75 / hour
Opens an external site
- Employment type
- Contract
- Experience level
- Mid-level · 2+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Canada
Job summary
The Data Quality Engineer will validate data ingestion, transformation, and movement across Bronze, Silver, and Gold cloud data layers. They are responsible for troubleshooting data defects and collaborating with engineering teams to ensure data integrity and business rule compliance.
Job details
Who We Are PLATO is Canada’s largest Indigenous-owned software testing and technology services company. For nearly 30 years, our expert teams have helped our clients deliver reliable products that users enjoy interacting with. Our 100% Canada‑based team brings deep experience in QA, software testing, and IT services, along with a shared commitment to collaboration, mentorship, and continuous improvement. We’re a team that shows up for each other, whether that’s tackling complex client challenges or helping colleagues grow through coaching and knowledge‑sharing. As Canada’s largest Indigenous‑owned software testing company, we’re proud of our roots and our mission to build a stronger, more inclusive technology workforce. At the same time, we warmly welcome applicants of all backgrounds and experiences who are passionate about quality, teamwork, and making an impact. Contract Duration: 15Nov26 to 31Jul27 Security Clearance: Current Secret level clearance is required at time of application. Job Summary We are seeking a detail-oriented Data Quality Engineer to ensure the accuracy, completeness, and integrity of data across modern cloud data platforms. This role is responsible for validating data ingestion, transformation, movement, and quality across Bronze, Silver, and Gold layers, ensuring business rules, lineage, and reporting requirements are met. The ideal candidate brings strong experience in ETL/ELT testing, data lake and lakehouse environments, SQL-based analysis, and Azure data technologies. Responsibilities Validate data ingestion, transformation, and movement across Bronze, Silver, and Gold data layers. Test data completeness, accuracy, conformity, lineage, business rules, and exception handling. Perform ETL/ELT, data warehouse, data lake, and lakehouse testing. Validate source-to-target mappings, schema changes, and transformation logic. Verify batch, incremental, and CDC (Change Data Capture) processing. Conduct large-volume data validation and reconciliation activities. Assess data quality, auditability, and end-to-end data lineage. Investigate and troubleshoot data defects using SQL and other analysis tools. Collaborate with engineering and business teams to ensure data solutions meet functional and quality requirements. Support test planning, defect tracking, and reporting activities using Azure DevOps or similar tools. Requirements Experience testing data pipelines, ETL/ELT processes, data warehouses, data lakes, or lakehouse solutions. Strong knowledge of data validation techniques, data quality controls, and source-to-target mapping. Experience validating structured and semi-structured data. Advanced SQL skills for data analysis, reconciliation, and defect investigation. Working knowledge of Python and PySpark for data testing and validation activities. Experience with Azure data technologies, including: Azure Databricks Azure Data Lake Storage (ADLS) Azure Data Factory (ADF) Delta Lake Kafka and/or Event Hub Azure DevOps Familiarity with data profiling and data quality tools. Strong analytical, problem-solving, and troubleshooting skills. Excellent attention to detail and ability to work effectively in a fast-paced, data-driven environment. Work With Us At PLATO, we believe that great work happens when people feel supported, connected, and challenged in the right ways. You’ll be part of a collaborative environment where experienced professionals share knowledge, mentor others, and contribute to solving complex, real‑world client projects. We are committed to inclusive hiring practices and encourage applications from individuals of all backgrounds, including women, persons with disabilities, visible minorities, and Indigenous peoples. If you require accommodation at any stage of the recruitment process, we’re here to support you. PLATO respectfully acknowledges that we operate on treaty territories, unceded First Nations and Inuit territories, and within Métis homelands. We honour the long history of these lands and actively work toward reconciliation between Indigenous and non‑Indigenous peoples on Turtle Island.
What you’ll do
The Data Quality Engineer will validate data ingestion, transformation, and movement across Bronze, Silver, and Gold cloud data layers. They are responsible for troubleshooting data defects and collaborating with engineering teams to ensure data integrity and business rule compliance.
Requirements
Candidates must have experience testing data pipelines, ETL/ELT processes, and data lakehouse solutions using Azure technologies. Proficiency in advanced SQL, Python, and PySpark is required, along with a current Secret level security clearance.
Listed skills
- SQL · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data Quality
- ETL/ELT Testing
- SQL
- Azure Databricks
- Azure Data Lake Storage
- Azure Data Factory
- Delta Lake
- Python
- PySpark
- Data Pipelines
- Data Warehousing
- Kafka
- Event Hub
- Azure DevOps
- Data Lineage
- Data Profiling
- Data Quality Assessment
- Change Data Capture (CDC)
- Semi-Structured Data
- Data Lakes
- Azure Data Lake
- Data Analysis
- Software Testing
- Microsoft Azure
- Reconciliation
- Continuous Improvement Process
- Data Validation
- Extract Transform Load (ETL)
- Defect Tracking
- Exception Handling
- Problem Solving
- IT Service Management
- Python (Programming Language)
- Mentorship
- Coaching
- Safety Assurance
- SQL (Programming Language)
- Test Data Generation
- Test Planning
- Troubleshooting (Problem Solving)
- Security Clearance
- Activities Of Daily Living (ADLs)
- Data Ingestion
- Data Layers
- Teamwork
- Apache Kafka
- Detail Oriented
Job areas
- Data & Analytics
- Software
- Technology
- Engineering
- Data Quality Engineer
- Data Engineer
- Software Developers
- Database Administrators
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