Pay Rate: $69/hr
Work Authorization Requirement: US Citizen or Green Card Holder
Position OverviewWe are seeking a Test Data Management Engineer (SDET) to support QA and development teams by mining, provisioning, and maintaining high‑quality test data across multiple environments. This role blends hands‑on technical work with problem‑solving, automation, and cross‑team collaboration. You will build repeatable solutions that accelerate testing, improve data accuracy, and strengthen overall delivery.
What You’ll DoFulfill data mining requests to identify, extract, and validate test data for project teams.
Create, provision, refresh, and maintain test data across multiple test environments.
Build and enhance automated solutions that streamline test data setup, delivery, and reuse.
Write, optimize, and troubleshoot SQL queries for analysis, validation, and issue resolution.
Perform API testing using tools such as Postman, SoapUI, or similar.
Collaborate with testers, developers, and stakeholders to understand data needs and deliver effective solutions.
Support root cause analysis for data‑related issues impacting testing or delivery timelines.
Identify opportunities to automate test data processes and improve efficiency.
Document processes, reusable components, and best practices for test data management.
Required QualificationsExperience supporting test data needs for QA/testing teams.
Strong SQL skills for data extraction, validation, and troubleshooting.
Experience with relational and cloud databases (Oracle, DB2, Postgres, BigQuery, SQL Server, etc.).
Hands‑on API testing experience (Postman, SoapUI, or similar).
Ability to work across multiple test environments and manage competing data requests.
Strong analytical, communication, and collaboration skills.
Exposure to mainframe applications, data structures, or testing processes.
Preferred QualificationsExperience with automation frameworks or scripting for test data creation and validation.
Familiarity with Test Data Management (TDM) tools.
Experience in large enterprise or regulated environments with complex data dependencies.
Understanding of data masking, data virtualization, data sub‑setting, and synthetic data creation.
Experience with Unix/Linux command‑line operations; exposure to Docker or containerized environments.