SDET - Test Data Management Engineer

Overview

Client is seeking a Test Data Management Engineer to support QA testing teams with data mining, test data provisioning, data validation, and automation. This role requires strong SQL skills, API testing experience, and the ability to support complex test environments. Exposure to mainframe systems and hands-on automation experience are strong pluses.

Core Responsibilities

• Complete data mining requests to identify, extract, and validate test data needed by project teams.
• Create, provision, refresh, and maintain test data across multiple test 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 use cases for test data automation.
• Document processes, reusable solutions, and best practices related to test data management.

Essential Qualifications, Skills, and Technologies

• 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, BigQuery, or SQL Server.
• Hands-on API testing experience using tools such as Postman, SoapUI, or similar solutions.
• Ability to work across multiple test environments and manage competing data requests.
• Exposure to mainframe applications, data structures, or testing processes.
• Strong problem-solving, communication, and collaboration skills.

Preferred Skills or Experience

• Experience with automation frameworks or scripting used to support test data creation and 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 subsetting, and synthetic data creation.
• Experience with Unix/Linux command-line operations.
• Exposure to Docker or containerized environments.

Work Details

• Hybrid role.
• Must be onsite 2 days per week at 4910 Tiedeman Rd, Brooklyn, OH 44144.