QA Engineer: Financial Systems Data Quality Lead

IBM; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

IBM Consulting is seeking a QA Engineer - Financial Systems to design and execute comprehensive data quality testing for data-intensive applications including ETL, BAO, MDM, and data migrations. You will plan, execute, and analyze tests, combining manual and automated approaches to ensure data integrity and quality across financial systems.

This role can be performed from anywhere in the U.S., requiring collaboration with cross-functional teams to translate business requirements into robust test

Qualifications

• Experience designing and executing data quality testing strategies for ETL, Big Data, and data-intensive applications.
• Experience with business requirements to craft optimized test scenarios ensuring data quality and integrity.
• Ability to plan and execute testing activities, estimate efforts, create test cases, and identify data needs.
• Proficiency in both manual and automated testing, defect tracking, and test result analysis.

Responsibilities

• Design testing strategies for ETL, BAO/MDM, and data migrations.
• Plan and execute testing activities, estimate efforts, create test cases, and identify test data requirements.
• Execute test cases using manual and automation tools and report status.
• Analyze test outcomes to drive continuous improvements.
• Develop optimized test scenarios aligned with business requirements.

Skills

Data quality testing

Test planning

Test automation

ETL testing

Big Data testing

Analytical thinking

Education

Bachelor's Degree

Tools

BAO

MDM

FIS

ETL tools

Job description

IBM Consulting is seeking a QA Engineer - Financial Systems to design and execute comprehensive data quality testing for data-intensive applications including ETL, BAO, MDM, and data migrations. You will plan, execute, and analyze tests, combining manual and automated approaches to ensure data integrity and quality across financial systems.

This role can be performed from anywhere in the U.S., requiring collaboration with cross-functional teams to translate business requirements into robust test