State Street
Financial Services
SeniorQAEngineer-AssistantManager
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior QA Engineer - Assistant Manager at State Street. Skills: QA, Data Engineering, Java, Spring Boot, Databricks, Apache Spark, AWS, Test Automation, Performance Testing, Data Quality Validation. Perform functional, integration, and regression testing for Java / Spring Boot applications and microservices. Validate APIs, backend services, and application workflows”
What You'll Achieve.
Timely execution of high-quality test cycles with minimal defect leakage; data quality validation outcomes; Contribution to improved automation and performance coverage
Industry & Context.
solve real problems
What They're Looking For.
Must Have
7–10 + years of experience in Quality Assurance / Testing roles, understanding of Java-based applications and backend testing concepts, Hands-on exposure to Databricks and Apache Spark data platforms, Good knowledge of data validation and SQL, Experience with test automation frameworks and tools, Understanding of performance testing concepts, Familiarity with AWS and cloud-based systems, Knowledge of software design patterns and enterprise QA best practices
Nice to Have
Experience working in banking or regulated enterprise environments, Exposure to AI / ML testing or data-driven platforms, Experience with CI/CD pipelines, Agile / Scrum experience, banking domain knowledge
What You'll Do.
and regression testing for Java / Spring Boot applications and microservices
and application workflows
Execute QA activities for Databricks and Apache Spark data pipelines
Perform data quality validation
Ensure data pipelines meet performance and scalability expectations
Develop and maintain test automation scripts
Execute and support performance
Analyze test results and work closely with developers to resolve defects
Support QA for AI / ML-enabled use cases
Adapt testing approaches to new tools
How You'll Work.
Team & Collaboration
closely working as part of global team; works closely with developers, QA Officers, and architects; Actively participate in design and code reviews; Work in Agile / DevOps teams; Collaborate with developers, senior QA members, and QA Officers; Positive collaboration with development and QA leadership teams
Process & Methodology
supporting sprint execution and release cycles
Full Job Description
**Role Summary:** Global Markets business has embarked on a technology transformation project to replace legacy front office applications with an extensible new application. This role is responsible for QA-Data Engineer of this application closely working as part of global team. We are looking for a Senior QA Developer with experience in building high-performing, scalable, enterprise-grade applications. You will be part of a talented software team that works on mission-critical applications. ## **Role Summary:** The Senior Associate – QA is a **hands‑on senior quality assurance role** responsible for ensuring **high quality, performance, and reliability** of enterprise **applications, data platforms, and AI‑enabled solutions** built using **Java, Spring Boot, Databricks, Apache Spark, and AWS**. The role focuses on **test execution, automation, data quality validation, and performance testing** , while strictly adhering to **banking standards, enterprise QA frameworks, and design patterns**. This position works closely with developers, QA Officers, and architects within Global Technology Services (GTS). ## ## **Key Responsibilities:** ### **Application Quality Assurance** * Perform functional, integration, and regression testing for **Java / Spring Boot applications** and microservices. * Validate APIs, backend services, and application workflows against functional and non‑functional requirements. * Ensure adherence to **approved design patterns, coding standards, and bank SDLC practices**. * Actively participate in design and code reviews from a **quality and testability perspective**. ### ### **Data & Platform Quality Assurance** * Execute QA activities for **Databricks and Apache Spark data pipelines**. * Perform **data quality validation** , including: * Accuracy, completeness, consistency, and timeliness checks * Data reconciliation and schema validation * Validation of transformations and aggregations * Ensure data pipelines meet **performance and scalability
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