QA Data Engineer

Job Title: QA Data Engineer
Location: [Remote]
Employment Type: Full time

About Us:
DMV IT Service LLC is a trusted IT consulting firm, established in 2020. We specialize in optimizing IT infrastructure, providing expert guidance, and supporting workforce needs with top-tier staffing services. Our expertise spans system administration, cybersecurity, networking, and IT operations. We empower our clients to achieve their technology goals with a client-focused approach that includes online training and job placements, fostering long-term IT success.

Job Purpose:
We are seeking a QA Data Engineer . This role will focus on developing and implementing test strategies, ensuring data accuracy, and optimizing data pipelines within the Google Cloud Platform (GCP) ecosystem. The ideal candidate will have a strong background in data engineering, test automation, and cloud technologies with expertise in SQL and a general understanding of BigQuery and Dataflow.

Requirements

• Partner with Data Engineers, Analysts, and business stakeholders to define quality requirements for data and applications.
• Document test cases, data validation rules, and best practices for scalable data governance.
• Develop and implement test cases for ETL/ELT pipelines, data transformations, and ingestion processes.
• Perform data validation, execute test cases (manual or automated), and analyze results to ensure high-quality data.
• Conduct regression testing to verify that error validation is present and reconcile variances or data anomalies.
• Validate data transformations and ingestion processes for both structured and unstructured data.
• Monitor and troubleshoot data issues, failures, and inconsistencies across the data pipeline.
• Provide support for root cause analysis and resolution of data-related defects, including identifying necessary code changes.
• Document and track defects, providing detailed reports to development teams for resolution.
• Participate in the design and implementation of automated testing scripts to improve testing efficiency.
• Conduct post-release and post-implementation validation of software performance in production environments.
• Continuously monitor and evaluate the quality of software deliverables, offering feedback for improvement opportunities.
• Collaborate with end-users to gather feedback and improve product quality.

Qualifications & Skills:

Must Have:

• 3-5+ years of experience in data engineering, data testing, or quality assurance.
• Proficiency in SQL and data validation frameworks (e.g., test strategies).
• Strong understanding of ETL/ELT processes, data modeling, and schema design.

Nice-To-Have:

• Familiarity with automated testing frameworks for data (e.g., Great Expectations, dbt tests).
• Familiarity with LL Bean data and business processes.
• Familiarity with GCP data services such as BigQuery, Dataflow, Dataproc, and Cloud Storage.
• Experience with Python.

Additional Skills:

• Strong understanding of software development and testing methodologies.
• Excellent analytical and problem-solving skills.
• High attention to detail and the ability to document defects accurately.
• Highly collaborative, with the ability to work effectively with cross-functional teams.
• Knowledge of Agile and Waterfall project management methodologies.
• Effective communication skills (both verbal and written) for collaborating with teams.
• Familiarity with programming languages (e.g., Java, Python) for automated testing and scripting.
• Ability to work independently and manage multiple tasks simultaneously.
• GCP or other relevant certifications in software testing are a plus.

Working Conditions:

• Ability to work in a fast-paced, dynamic environment.