Data Platforms QA Engineer: Data Quality & Pipelines

Resolve Tech Solutions; Irving (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

Resolve Tech Solutions is hiring for a QA/Quality Engineer role focused on data-intensive marketing tech environments. The role involves testing data pipelines, validating data models, and building automated quality checks to ensure accuracy across audiences, features, and attributes.

You will collaborate with data science and engineering teams to validate production features and maintain data contracts, while enforcing privacy and compliance standards in testing scopes.

Qualifications

• 5+ years of experience in a quality assurance or quality engineering role in data-intensive environments.
• Hands-on experience testing data pipelines, ETL/ELT processes, and data platforms.
• Strong SQL skills for data validation and exploratory testing.
• Experience with test automation tools and frameworks (pytest, Selenium).
• Familiarity with CI/CD pipelines and integrating quality gates into release workflows.
• Experience with defect tracking and test management tools (Jira, TestRail).
• Understanding of data quality dimensions (accuracy, completeness, timeliness).

Responsibilities

• Define and execute comprehensive test plans and regression suites for data pipelines.
• Validate data models and feeds to decisioning systems for accuracy and completeness.
• Design data-quality validation frameworks and automated test scripts.
• Verify data attributes delivered to activation platforms against requirements.
• Collaborate with data science and engineering on model features and data contracts.
• Provide metrics and risk assessments to leadership.

Skills

QA Experience

SQL skills

Test Automation

CI/CD pipelines

Jira / TestRail

Tools

pytest

Selenium

Job description

Resolve Tech Solutions is hiring for a QA/Quality Engineer role focused on data-intensive marketing tech environments. The role involves testing data pipelines, validating data models, and building automated quality checks to ensure accuracy across audiences, features, and attributes.

You will collaborate with data science and engineering teams to validate production features and maintain data contracts, while enforcing privacy and compliance standards in testing scopes.