Tentek
We are seeking a Senior QA Engineer to join our growing team of data management and analytics professionals. In this role, you will lead and execute comprehensive testing strategies for data pipelines, ETL processes, reporting, and dashboard solutions. As a senior team member, you will drive automation initiatives, establish quality best practices, and serve as a key quality advocate across cross-functional teams. You will be responsible for ensuring data integrity, system performance, and high-quality deliverables in a dynamic and collaborative environment.
Key Responsibilities:
1. Quality Leadership & Strategy:
o Lead quality assurance efforts across the data lifecycle, from ingestion to visualization.
o Define and implement robust QA strategies, standards, and processes for data validation, transformation, and reporting accuracy.
o Mentor junior QA engineers and promote a culture of quality across engineering teams.
2. Advanced Testing Execution:
o Design, manage, and execute test plans to validate data completeness, accuracy, consistency, and performance across reporting and dashboard solutions.
o Conduct advanced data profiling and exploratory testing to uncover systemic data issues.
3. Automation & Framework Development:
o Develop, enhance, and maintain automated test suites and frameworks to support continuous integration and regression testing of data solutions.
o Partner with data engineers to integrate automated testing into CI/CD pipelines.
4. Cross-Functional Collaboration:
o Collaborate with engineering, analytics, product management, and business stakeholders to translate business requirements into test cases and quality metrics.
o Serve as the QA point of contact for data governance, engineering reviews, and UAT sessions.
5. Data Governance & Quality Standards:
o Establish and enforce best practices for data quality assurance and validation.
o Contribute to enterprise-wide data governance efforts to uphold standards for data accuracy and consistency.
6. Performance Monitoring & Issue Resolution:
o Design and maintain QA dashboards and KPIs to track data quality trends and highlight anomalies.
o Proactively monitor and troubleshoot performance bottlenecks in data pipelines.
o Lead root cause analysis for complex data issues and drive resolution in collaboration with engineering teams.
7. Documentation & Reporting:
o Maintain thorough documentation of test cases, processes, and defect reports.
o Communicate test findings, risks, and recommendations to technical and non-technical stakeholders.
Basic Qualifications • Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. • 5+ years of experience in data quality assurance, preferably with a focus on data pipelines, reporting, and analytics solutions. • Expertise in data testing methodologies, including data profiling, boundary and regression testing, and performance testing. • Proficiency in SQL and Python for data validation and automation. • Experience with QA frameworks and tools such as PyTest, Great Expectations, dbt tests, or similar. • Familiarity with BI and reporting tools (e.g., Tableau, Power BI) to validate end-user dashboards and visualizations. • Strong understanding of data management principles, including data mapping, data lineage, and metadata management. • Proven ability to lead initiatives, mentor peers, and influence quality standards across teams. • Experience working in Agile/Scrum environments with a strong commitment to iterative development and continuous improvement. • Excellent problem-solving, communication, and stakeholder management skills.
Required Education • Bachelor's degree in Computer Science, Information Technology, or related.
Key Responsibilities:
1. Quality Leadership & Strategy:
o Lead quality assurance efforts across the data lifecycle, from ingestion to visualization.
o Define and implement robust QA strategies, standards, and processes for data validation, transformation, and reporting accuracy.
o Mentor junior QA engineers and promote a culture of quality across engineering teams.
2. Advanced Testing Execution:
o Design, manage, and execute test plans to validate data completeness, accuracy, consistency, and performance across reporting and dashboard solutions.
o Conduct advanced data profiling and exploratory testing to uncover systemic data issues.
3. Automation & Framework Development:
o Develop, enhance, and maintain automated test suites and frameworks to support continuous integration and regression testing of data solutions.
o Partner with data engineers to integrate automated testing into CI/CD pipelines.
4. Cross-Functional Collaboration:
o Collaborate with engineering, analytics, product management, and business stakeholders to translate business requirements into test cases and quality metrics.
o Serve as the QA point of contact for data governance, engineering reviews, and UAT sessions.
5. Data Governance & Quality Standards:
o Establish and enforce best practices for data quality assurance and validation.
o Contribute to enterprise-wide data governance efforts to uphold standards for data accuracy and consistency.
6. Performance Monitoring & Issue Resolution:
o Design and maintain QA dashboards and KPIs to track data quality trends and highlight anomalies.
o Proactively monitor and troubleshoot performance bottlenecks in data pipelines.
o Lead root cause analysis for complex data issues and drive resolution in collaboration with engineering teams.
7. Documentation & Reporting:
o Maintain thorough documentation of test cases, processes, and defect reports.
o Communicate test findings, risks, and recommendations to technical and non-technical stakeholders.
Basic Qualifications • Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. • 5+ years of experience in data quality assurance, preferably with a focus on data pipelines, reporting, and analytics solutions. • Expertise in data testing methodologies, including data profiling, boundary and regression testing, and performance testing. • Proficiency in SQL and Python for data validation and automation. • Experience with QA frameworks and tools such as PyTest, Great Expectations, dbt tests, or similar. • Familiarity with BI and reporting tools (e.g., Tableau, Power BI) to validate end-user dashboards and visualizations. • Strong understanding of data management principles, including data mapping, data lineage, and metadata management. • Proven ability to lead initiatives, mentor peers, and influence quality standards across teams. • Experience working in Agile/Scrum environments with a strong commitment to iterative development and continuous improvement. • Excellent problem-solving, communication, and stakeholder management skills.
Required Education • Bachelor's degree in Computer Science, Information Technology, or related.