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Data Quality Assurance Engineer (Mid-level)

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Summary

Mid-level QA engineer performing quality assurance for enterprise data management and the data development lifecycle — reviewing requirements, drafting test cases, running accuracy/latency/performance/security gate checks, logging defects in Azure DevOps, and maintaining automated regression checks. Core stack: SQL, Python, ETL/ELT testing; Databricks and Tableau are pluses.

Salary: ₱50,000 – ₱75,000 per month

Job Description:

• Perform quality assurance and quality control duties for the Enterprise Data Management and data development life cycle.

• Participate in backlog refinement; review requirements and technical specifications and draft acceptance criteria and test cases before development starts.

• Execute the practice quality gate checks (accuracy, latency, performance, security) for assigned work items and report results.

• Document defects in Azure DevOps with clear reproduction steps and supporting evidence; retest fixes.

• Maintain and execute assigned automated regression checks; contribute new automated checks with guidance.

• Work with business analysts and developers to clarify scope and expected results.


Required Key Knowledge Skills/ Experience:

• 2+ years in QA testing, preferably in a data engineering or data warehousing environment.

• Solid SQL for data validation and reconciliation; basic Python scripting.

• Experience testing ETL/ELT loads or data warehouse changes.

• Experience with defect and test management tooling (Azure DevOps or equivalent).

• Good verbal and written communication skills.

• Superior problem-solving skills, self-motivation and the capacity to work under pressure and on tight deadlines.

• Demonstrated ability to learn and utilize new technologies, disciplines and frameworks as needed.

• Familiarity with Agile/Scrum methodologies.


Preferred Experience:

• Hands-on experience with Databricks (PySpark, Delta Lake, Databricks Workflows/Jobs) or other Big Data/Spark platforms

• Exposure to data test automation frameworks (e.g., pytest, dbt tests)

• Exposure to Tableau or other BI reporting layers

• Banking or financial services industry experience


Education requirements:

• Bachelor's Degree in Computer Science, Information Systems, Computer Engineering or related field.

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