As a Test & Data Quality Consultant, you will support testing and data quality activities across analytics solutions, ensuring data is accurate, complete, and fit for business use throughout delivery and production readiness.
What You’ll Do and How You’ll Succeed
Test Strategy & Planning
- Develop and execute test scenarios, test cases, and acceptance criteria based on business and technical requirements.
- Support test planning and coordinate testing activities across business and technical teams.
- Identify testing risks, dependencies, and potential data quality issues.
Data Validation & Quality Assurance
- Perform data validation, reconciliation, and quality checks to ensure accuracy and completeness.
- Test ETL/ELT processes and data transformation workflows.
- Perform quality assurance and validation of Power BI reports, dashboards, and datasets.
- Log, track, and support the resolution of defects and data issues.
Delivery & Readiness
- Support UAT execution, defect management, and production readiness activities.
- Validate testing outcomes against business requirements and analytics objectives.
- Collaborate with developers, data engineers, business users, and other stakeholders to resolve issues and ensure quality deliverables.
We’d Love to Hear From You If...
Experience
- You have 5–8 years of experience in testing, data quality, analytics QA, or a related field.
- You have hands-on experience testing data and analytics solutions.
- Experience working in enterprise data, BI, or digital transformation projects is preferred.
Technical Expertise
- You have a strong understanding of ETL/ELT processes, data validation, and data reconciliation.
- You have experience with Power BI testing, including reports, dashboards, datasets, and data accuracy validation.
- You have a good understanding of data quality principles and testing methodologies.
- Experience with SQL for data validation and reconciliation is preferred.
Ways of Working
- You demonstrate strong test execution, defect tracking, and issue management skills.
- You are detail-oriented and able to identify data inconsistencies and quality issues.
- You collaborate effectively with both business and technical stakeholders.
- You can work independently while contributing effectively within a project team.