QA Data Enginee

Key Responsibilities:

• Partner with Data Engineers, Analysts, and business stakeholders to define quality requirements.
• Document test cases, data validation rules, and best practices for scalable data governance.
• Develop and implement test cases for ETL/ELT pipelines, data transformation, and ingestion processes.
• Perform data validation, execute test cases (manual or automated) and analyze results. Regression testing ensures sufficient error validation is present. Reconcile variances and data anomalies to ensure high-quality data.
• Validate data transformations and ingestion processes for structured and unstructured data.
• Monitor and troubleshoot data issues, failures, and inconsistencies across the pipeline.
• Provide support for root cause analysis and resolution of data-related defects, including the identification of 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 regression testing to ensure that new code changes do not adversely affect existing functionality.
• Perform post-release and post-implementation validation of software performance in production environments.
• Continuously monitor and evaluate the quality of software deliverables, providing feedback for improvement opportunities.
• Collaborate with end users to gather feedback.

Qualifications & Skills:

Must Have:

• 3-5+ years of experience in data engineering, data testing, or quality assurance.
• Proficiency in SQL, and data validation frameworks. (test strategies).
• An 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 process.
• Familiarity with GCP data services (BigQuery, Dataflow, Dataproc, Cloud Storage) and Python.

Additional:

• Strong understanding of software development and testing methodologies.
• Excellent analytical and problem-solving skills.
• Attention to detail and ability to document defects accurately.
• Highly collaborative. Effectively works with cross-functional teams for the support and performance of the EDP and packaged applications.
• Strong understanding of project management methodologies, including Agile and Waterfall.
• Effective communication skills, both written and verbal, to collaborate with cross-functional teams.
• Familiarity with programming languages (e.g., Java, Python) and scripting for automated testing.
• Ability to work independently and manage multiple tasks simultaneously.
• GCP or other relevant certification in software testing.