This position is posted by Jobgether on behalf of a partner company. We are currently looking for a GCP Data Quality Test Engineer with Retail Domain in the United States.
We are seeking a skilled Data Quality Test Engineer to ensure the accuracy, integrity, and performance of data pipelines within the Google Cloud Platform (GCP) ecosystem. In this role, you will collaborate closely with data engineers, analysts, and business stakeholders to define quality requirements, develop and execute test cases, and validate both structured and unstructured data. You will contribute to automated testing strategies, monitor data quality, and help optimize data processes to support critical retail operations. This role combines hands-on technical work with a strong focus on maintaining high standards of data governance and business alignment.
Accountabilities:
- Partner with data engineering, analytics, and business teams to define data quality and validation requirements.
- Develop, document, and implement test cases for ETL/ELT pipelines, data transformations, and ingestion processes.
- Perform data validation, regression testing, and reconciliation to ensure accurate and high-quality data.
- Monitor data pipelines, troubleshoot inconsistencies, and support root cause analysis of defects.
- Implement and maintain automated testing scripts and frameworks to improve testing efficiency.
- Conduct post-release validation and provide feedback for continuous improvement of data deliverables.
- Collaborate with end users to gather feedback and ensure alignment with business needs.
Requirements
- –5+ years of experience in data engineering, data testing, or quality assurance.
- Strong proficiency in SQL and data validation frameworks.
- Hands-on experience with GCP data services (BigQuery, Dataflow, Dataproc, Cloud Storage) and Python.
- Experience with automated data testing frameworks (e.g., Great Expectations, dbt tests).
- Ability to create and execute test cases aligned with business and technical requirements.
- Experience integrating and validating retail domain data.
- Nice-to-have: understanding of ETL/ELT processes, data modeling, schema design, and organizational business processes.
Benefits
- Remote-friendly position with flexibility to work from home.
- Opportunity to work on large-scale retail data platforms and cloud technologies.
- Exposure to modern data quality and automation frameworks.
- Collaborative, technology-driven environment with focus on skill growth and impact.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias, focusing solely on your fit for the role.
Once the shortlist is completed, it is shared directly with the company that owns the job opening. The final decision and next steps (such as interviews or assessments) are then managed by their internal hiring team.
