QA Data specialist
financial technology
QADataspecialist-SoftwareDevelopmentEngineerinTestII
Neural analysis suggests this role is
optimal for Mid candidates.
“QA Data specialist - Software Development Engineer in Test II at QA Data specialist. Skills: Data Engineering, AI/ML, Testing Frameworks, Data Validation. Design test strategies for data pipelines and AI systems. Validate data transformations, ETL/ELT processes”
What You'll Achieve.
reduce the “time to market” for products; ensuring quality; meet quality acceptance criteria; ensure optimal user experience and system scalability; drive continuous improvement initiatives
Industry & Context.
risk mitigation strategies; data-driven decision making
What They're Looking For.
Must Have
3+ years of experience in software testing or development, deep understanding of testing methodologies, coding, debugging, hands-on experience with data quality testing and validation across data engineering platforms, Proficiency in programming languages such as Python, Java, or C#, SQL/PL-SQL skills for database interactions and data validation, experience with big data processing languages such as PySpark or Scala for testing data pipelines, Hands-on experience with data engineering and analytics platforms such as Databricks, Microsoft Fabric, or Azure Data Factory, business intelligence tools like Power BI, Tableau, or similar visualization platforms for testing dashboards and reports, Experience designing and developing automated testing frameworks using tools such as AccelQ, Tosca, Selenium, Pytest, or Great Expectations, ability to create test automation for multiple layers including UI, API, Services, and data validation, understanding of ETL/ELT processes, data warehousing concepts, data lake architectures, ability to validate data transformations, data quality rules, and end-to-end data pipeline workflows, Familiarity with Agile/Scrum methodologies, CI/CD practices, version control systems such as Git, GitHub, or Azure DevOps, experience working in collaborative, fast-paced development environments
Nice to Have
Experience with AI-driven testing tools and platforms, machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, demonstrated ability to implement intelligent test optimization and predictive analytics for quality assurance, Knowledge of cloud platforms such as Azure, AWS, or GCP, experience in testing cloud-native data solutions, serverless architectures, containerization technologies such as Docker, Kubernetes, or Azure Container Instances, Exposure to data quality frameworks and tools such as Apache Griffin, Deequ, or Monte Carlo, understanding of data observability practices, data lineage tracking, metadata management, experience with data pipeline technologies including Databricks Delta Live Tables (DLT) for ensuring end-to-end data quality, Experience with Behavior Driven Development (BDD) frameworks such as Cucumber or SpecFlow, performance testing tools like JMeter or Locust, familiarity with API testing tools such as Postman, REST Assured, or SoapUI
What You'll Do.
Design test strategies for data pipelines and AI systems
Validate data transformations
Implement AI algorithms for test optimization
Collaborate with data engineering
Develop and execute performance testing strategies
Provide technical guidance on QA and automation
Gather quality metrics for improvement
How You'll Work.
Team & Collaboration
Collaborate with data engineering, development, and business intelligence teams; Participate in sprint planning, technical reviews, and requirement analysis sessions; Provide technical guidance to the development team; Collaborate in an Agile environment; Collaborate with different internal teams
Full Job Description
# **About the Role:** **Grade Level (for internal use):** 09 **The** **Role:** QA Data Specialist - Software Development Engineer in Test II **The Team:** Our central data and reporting function serve as the organizational hub for all data spanning financials to inventory, uniquely positioning us to innovate and build cutting-edge data products and AI/ML solutions for internal stakeholders. We foster a collaborative environment that values experimentation, data-driven decision making, and continuous learning, where team members regularly share knowledge about the latest AI developments and methodologies. The team maintains a culture of intellectual curiosity where experienced practitioners mentor team members and provide meaningful projects that contribute to real-world applications. **The Impact:** As a Quality Engineer managing AI systems, you will play a crucial role in developing and optimizing testing frameworks that utilize AI algorithms to enhance the testing process across Web/Mobile/API/Services. Your challenge will be to reduce the “time to market” for products while ensuring quality, by implementing AI-driven test optimization techniques. You will work with a variety of advanced technologies and collaborate with different internal teams. **What’s in it for you:** * Collaborate with a team of highly skilled, ambitious, and result-oriented professionals focused on AI advancements. * Utilize cutting-edge AI technologies to innovate testing methodologies and enhance automation. * Experience a dynamic environment that allows you to think and act like a developer while fulfilling QA responsibilities. * Engage in a culture that promotes urgency and proactive approaches in quality assurance. * Opportunities for skill enhancement, knowledge sharing, and innovation in AI-driven testing solutions. * Build a rewarding career with a global leader in financial technology. **Responsibilities:** * Design and develop comprehensive test strategies for data engineering pipe
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