QA Analyst
Bounteous is a premier end-to-end digital transformation consultancy dedicated to partnering with ambitious brands to create digital solutions for today’s complex challenges and tomorrow’s opportunities. With uncompromising standards for technical and domain expertise, we deliver innovative and strategic solutions in Strategy, Analytics, Digital Engineering, Cloud, Data & AI, Experience Design, and Marketing.
Our Co-Innovation methodology is a unique engagement model designed to align interests and accelerate value creation. Our clients worldwide benefit from the skills and expertise of over 4,000+ expert team members across the Americas, APAC, and EMEA. By partnering with leading technology providers, we craft transformative digital experiences that enhance customer engagement and drive business success.
We are seeking a QA Analyst, to drive strategic growth across our QA ecosystem. This role is responsible for that would help with validating and testing our reporting.
Description of what we are looking for:
Role and Responsibilities
- Quality Assurance Execution: Execute comprehensive test cases, identify data discrepancies, and document defects to ensure the integrity and accuracy of our data pipelines and reporting structures.
- Data Validation & Verification: Query and analyze complex data sets to verify that information processing through our systems aligns perfectly with established business logic and specifications. A strength here is a must.
- Process Optimization: Contribute to maintaining and continuously improving QA documentation, standard operating procedures, and testing frameworks to ensure repeatable, scalable processes.
Preferred Qualifications:
- Professional QA Experience: 3+ years of experience operating within a dedicated software or data quality assurance environment, with a proven track record of accurate defect tracking and reporting.
- Data Literacy: Demonstrated experience working directly with data structures, including a foundational understanding of relational databases and data manipulation.
- Analytical & Critical Thinking: Strong problem-solving skills with a keen eye for detail and the ability to conduct root-cause analysis on data anomalies.
- Communication Skills: Excellent verbal and written communication skills, with the ability to articulate technical issues and defects clearly to cross-functional stakeholders.
Preferred Skills (Optional)
Experience with the following tools is considered an asset but is not required:
- Foundational knowledge of SQL or exposure to cloud-based data warehouses such as Google BigQuery.
- Familiarity with enterprise data visualization and business intelligence tools (e.g., Looker, Tableau).
- Basic exposure to Python scripting or the ability to read and interpret code.