Test Data Engineer (Hybrid)

Signet Jewelers•Irving, TX

7d•Hybrid

About The Position

We are seeking a hands‑on Senior Test Data Engineer to own and advance Signet’s non‑production test data ecosystem. In this role, you will design modern Test Data Management (TDM) practices, stabilize lower environments, and build automation that provisions, validates, and monitors test data at scale. Your work will accelerate high‑quality releases across engineering teams by ensuring that test data is consistent, privacy‑safe, and continuously reliable across all lower environments. This role blends architecture and deep engineering: you will define strategy, build open‑source tooling, govern data quality, and lead cross‑team collaboration to enable fast, stable, and testable delivery pipelines.

Requirements

5+ years of experience in Test Data Engineering, Data Engineering, or Quality Engineering.
Strong expertise in SQL, data modeling, ETL/ESB pipelines, and job orchestration.
Hands‑on experience with TDM practices including subsetting, masking/anonymization, synthetic data creation, and referential integrity.
Automation first mindset using open‑source tools: Python, shell scripting, REST, Postman, Git, CI pipelines.
Proven experience stabilizing lower environments, identifying drift, and troubleshooting cross-system data issues.
Experience building automated validations, data quality checks, metrics, and monitoring/alerting.

Nice To Haves

Experience in retail or ecommerce domains.
Familiarity with platforms such as SAP Hybris, Sterling Order Management (DOM), ETL, ESB, PIM, Payment/PLCC systems.
Experience integrating test data flows with automated testing frameworks: Selenium, Cypress, Postman, REST Assured.
Background in inventory synchronization, environment observability, or data governance frameworks.
Experience with pipeline orchestration tools, cloud data platforms, or data virtualization technologies.

Responsibilities

Own the Test Data Strategy & Architecture
Define the end‑to‑end test data strategy across all lower environments to ensure consistency, accuracy, privacy, safety, and reuse.
Standardize and maintain reusable, versioned datasets, refresh cadences, and cross‑system referential integrity.
Develop and maintain modern TDM frameworks including subsetting, masking/anonymization, and synthetic data generation.
Reduce environment specific workarounds by implementing scalable, automated refresh mechanisms.
Build Technical Provisioning, Automation & Tooling
Build and maintain open‑source automation (Python, shell, REST, Postman, Selenium) for on‑demand data provisioning, masking, synthetic generation, and data validations.
Architect, optimize, and monitor extract jobs and pipelines in partnership with Lower Environments, ETL, ESB, PIM, and Order Management teams.
Implement parameterized pipelines and frameworks that enable rapid provisioning for complex test scenarios.
Integrate data provisioning workflows into CI pipelines and test automation frameworks.
Environmental Stability & Observability
Improve lower‑environment stability by detecting and remediating data drift, config drift, and schema drift across platforms.
Define and enforce SLAs related to environment readiness and test data availability.
Implement data quality gates and observability at pipeline, including automated health checks, dashboards, alerts.
Partner with support teams to build dashboards that proactively detect data quality issues and flag readiness gaps.
Governance, Quality & Risk Management
Establish governance rules, protect designated shared test SKUs, and enforce data integrity standards.
Ensure proper review, traceability, and documentation of changes using Jira and Confluence.
Lead efforts to ensure regression and integration suites always have reliable, stable, and privacy‑compliant test data.
Cross‑Team SME Leadership
Serve as the primary subject matter expert and escalation point for all test data concerns.
Mentor engineers, conduct design reviews for new data feeds, and guide teams in building testable and resilient data flows.
Partner closely with QE, Dev, Product, Ops, and Architecture teams to align test data strategy with delivery needs.
Documentation & Continuous Improvement
Maintain clear documentation including data models, runbooks, job flows, TDM frameworks, and environment health guides.
Track enhancements, issues, and KPIs through Jira to drive measurable continuous improvement.
Lead initiatives that reduce manual setup, accelerate test scenario enablement, and improve synchronization performance.