SDET Test Data Management Engineer # 26-12457

We are seeking a Test Data Management Engineer to support testing teams by fulfilling data mining requests, provisioning and maintaining test data, and building automated solutions that improve speed, accuracy, and repeatability. This role requires strong technical skills in SQL and API testing, with experience supporting complex test environments. Exposure to mainframe systems, and hands-on automation experience is a strong plus., * Complete data mining requests to identify, extract, and validate test data needed by project teams.

• Support teams by creating, provisioning, refreshing, and maintaining test data across environments.
• Build and enhance automated solutions to streamline test data setup, delivery, and reuse.
• Write and troubleshoot SQL queries for data analysis, validation, and issue resolution.
• Perform API testing and support validation of services that create, update, or consume test data.
• Partner with testers, developers, and stakeholders to understand data needs and deliver solutions.
• Support root cause analysis and resolution of data issues impacting delivery timelines.
• Identify different use cases for test data automation.
• Document processes, reusable solutions, and best practices related to test data management.

• Experience supporting test data needs for QA testing teams.
• Strong SQL skills for data extraction, validation, and troubleshooting.
• Experience working with databases such as Oracle, DB2, Postgres, Big Query, SQL Server etc.
• Hands-on experience with API testing using tools such as Postman, SoapUI, or similar solutions.
• Ability to work across multiple test environments and manage competing data requests.
• Strong problem-solving, communication, and collaboration skills.
• Exposure to mainframe applications, data structures, or testing processes., * Experience with automation frameworks or scripting used to support test data creation & validation.
• Familiarity with industry-standard Test Data Management tools.
• Experience working in regulated or large enterprise environments with complex data dependencies.
• Understanding of data masking, data virtualization, data sub-setting & synthetic data creation.
• Experience in Unix/Linux command-line operations with exposure to Docker and containerized environments.

Education & Certifications

• Bachelor's or equivalent experience