Quality Engineer / Test Automation

Bank of America•Addison, IL

2d•Onsite

About The Position

At Bank of America, the role supports the company’s purpose of helping make financial lives better through Responsible Growth. The company emphasizes an inclusive, caring workplace, teammate development and wellness, and an in-office culture that supports collaboration, engagement, and career development, with flexibility based on role responsibilities and business needs. This role tests and delivers complex software requirements to achieve business outcomes and ensures testing strategies and processes are well-defined and continuously improved. It establishes test and automation strategies, creates common test frameworks, and defines and manages testing processes, including test data generation, defect management, reporting, compliance, and traceability. The position is an automation-focused software engineering role supporting ETL/Data Engineering, Mainframe, and real-time data replication environments. It bridges Development Engineering and Quality Engineering, aligning ETL solution development, automated validation frameworks, testability, and shift-left quality practices. The engineer embeds automation, data validation, observability, and testability throughout the development lifecycle, and supports Unit, Feature, and Integrated automation testing for mission-critical data services. The role owns data integrity, transformation accuracy, replication reliability, and automated validation across high-volume integration and streaming platforms.

Requirements

At least 5 years of applicable software engineering, test automation, data engineering, or quality engineering experience.
Experience developing and supporting ETL/DataStage solutions, real-time data replication platforms, and large-scale data integration processes, with a focus on automation and quality engineering.
Experience designing, developing, and maintaining automated test frameworks or suites for Unit, Feature, Integrated, regression, and data validation testing.
Ability to own automated source-to-target validation, transformation accuracy, data integrity, reconciliation, and consistency across high-volume replication and streaming platforms.
Working knowledge of CI/CD practices and integrating automated tests, quality gates, and results reporting into delivery pipelines.
Hands-on engineering expertise across Mainframe, DataStage, IIDR/CDC, and Kafka-based data pipelines, including development, troubleshooting, automated testing, and validation.
Strong analytical, coding, problem-solving, communication, and cross-functional collaboration skills.
Skills listed: Analytical Thinking, Business Acumen, Influence, Technical Strategy Development, Test Engineering Automation, Collaboration, Solution Delivery Process, Solution Design, Stakeholder Management, Agile Practices, Application Development, Architecture, DevOps Practices, User Experience Design, and Shift-left.

Nice To Haves

Experience building reusable automation frameworks for data-intensive, high-volume, and business-critical environments.
Experience working in Agile delivery teams and influencing automation strategy across application, infrastructure, data, and quality engineering partners.
Ability to clearly communicate quality risks, automation coverage, dependencies, and business outcomes to technical and non-technical stakeholders.
Listed technologies and tools: ETL, Kafka, Mainframe, IIDR, Raft, Java, Co-Pilot, Octane, Litmus, DataStage, Python, AI Agents, SQL, UFT, Para Soft, GitHub, and Bit-Bucket.

Responsibilities

Create and optimize test processes, including defect management and reporting.
Create and optimize test automation frameworks and the use of test automation tools.
Lead test planning for complex features spanning platforms or multiple teams.
Create a test automation strategy across the application stack, including UI, API, and backend.
Ensure test cases are aligned with and signed off by business and other stakeholders.
Manage test execution and resolve, communicate, or escalate issues that may cause test plan variance.
Design test data and ensure data compliance requirements are met across all test environments.
Establish test and automation strategies and common test frameworks.
Define and manage testing processes, including test data generation, defect management, reporting, and traceability.
Support Unit, Feature, and Integrated automation testing for mission-critical data services.
Own automated source-to-target validation, transformation accuracy, data integrity, reconciliation, and consistency across high-volume replication and streaming platforms.
Integrate automated tests, quality gates, and results reporting into delivery pipelines.
Serve as a technical bridge between Development Engineers and Quality Engineers, promoting testability and shift-left quality practices.