As a Quality Automation Engineer III specializing in EDW and ETL testing, you are our data quality control anchor. You will ensure that our enterprise data pipelines, data warehouses, and downstream analytics applications are highly stable, accurate, and built with integrity. You will play a pivotal role in designing, creating, and automating data-centric testing frameworks to ensure complete data integrity across complex, interrelated backend systems. You will use your strong analytical and advanced SQL problem-solving skills to ensure our data platforms perform optimally. If you are a curious tester who isn't afraid to ask "why," thrives on uncovering complex data discrepancies, and loves collaborating in a team environment, you will thrive here. What You'll Do Design & Build Data Automation: Oversee, design, review, build, and deploy automated test solutions and frameworks tailored for complex EDW/ETL pipelines to ensure backend data processing meets rigorous quality standards. Root Cause Analysis: Lead the troubleshooting and triage of complex data issues and system escalations. Work closely with data engineering teams to identify root causes (such as data truncation, transformation logic errors, or performance bottlenecks) and implement long-term process improvements. Mentorship & Framework Governance: Guide and mentor other Test Automation Engineers to ensure their data-validation scripts align with our core automation frameworks, query optimization standards, and industry best practices. Cross-Functional Collaboration: Collaborate closely with Product Management, Data Architects, Developers, and business stakeholders to align on testing objectives, data schemas, and mapping requirements. End-to-End Testing: Write and execute robust manual and functional test cases when data exploration is required, transforming stable test patterns into automated regression suites. Values-Driven Execution: Always take action using Integrity, Caring, and Excellence to achieve all-win outcomes for our data consumers and the organization. What You'll Need (Required Skills) Education: Bachelor's degree in a technical field (Computer Science, Data Analytics, CIS) or equivalent professional experience. Core EDW/ETL Expertise: Strong, demonstrated experience in Enterprise Data Warehouse (EDW) and ETL testing methodology. Deep understanding of data mapping, data lineage, and data warehouse architectures. Advanced SQL: Expertise in writing complex SQL queries (e.g., multi-table joins, subqueries, analytical functions) to validate data transformations and aggregate large datasets. Test Automation Experience: 4+ years of test automation experience, including experience developing functional, load, and batch testing automation solutions. Programming Background: Expertise in Java and a strong understanding of Object-Oriented Programming (OOP) concepts. Automation Frameworks: Experience using UI and API test frameworks (such as Selenium or REST-assured) paired with programming languages to build end-to-end regression paths. Problem Solving & Debugging: Expertise in independently identifying backend technical issues, database misconfigurations, and defects in application or ETL code. Version Control: Hands-on experience with a distributed version-control management system like Git. Quality Advocacy: Expert knowledge of the role of Test Automation and Software Quality Assurance across the entire Software Development Life Cycle (SDLC). Additional Preferred Skills Testing Tools & Frameworks: Experience with testing frameworks/tools such as JUnit, TestNG, Cucumber (BDD), Appium, JMeter, or SoapUI/Postman. DevOps & CI/CD Pipeline Integration: Functional knowledge of DevOps practices, including tools like Jenkins, Maven, or similar CI/CD orchestrators to trigger automated data validation jobs. Non-Functional Testing: Exposure to non-functional testing protocols, specifically Data Performance/Load testing, Security, and Accessibility testing.
Job Responsibilities
- Design & Build Data Automation: Oversee, design, review, build, and deploy automated test solutions and frameworks tailored for complex EDW/ETL pipelines to ensure backend data processing meets rigorous quality standards.
- Root Cause Analysis: Lead the troubleshooting and triage of complex data issues and system escalations. Work closely with data engineering teams to identify root causes (such as data truncation, transformation logic errors, or performance bottlenecks) and implement long-term process improvements.
- Mentorship & Framework Governance: Guide and mentor other Test Automation Engineers to ensure their data-validation scripts align with our core automation frameworks, query optimization standards, and industry best practices.
- Cross-Functional Collaboration: Collaborate closely with Product Management, Data Architects, Developers, and business stakeholders to align on testing objectives, data schemas, and mapping requirements.
- End-to-End Testing: Write and execute robust manual and functional test cases when data exploration is required, transforming stable test patterns into automated regression suites.
- Values-Driven Execution: Always take action using Integrity, Caring, and Excellence to achieve all-win outcomes for our data consumers and the organization.