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Data Quality Manager

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Onsite

Data Quality Manager

Viventis Search Asia

Data Quality Manager

Skills

Data EngineeringPHPTesting & QA

17 days ago

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Important information


Contract type:

Permanent

Location:

Taguig, Metro Manila, Philippines

Work mode:

Onsite

Published on:

7 October 2026

What they need


WE'RE LOOKING FOR DATA QUALITY MANAGERS/DATA QA MANAGERS!

  • Work Shift: US Pacific Time/Night Shift
  • Work Setup: Hybrid – 3 days onsite per week
  • Salary: Up to Php 130,000 per year

ROLE OVERVIEW:

We are seeking an experienced Data QA Manager to lead a QA team and oversee quality assurance across data pipelines, ETL/ELT processes, data warehouse releases, and data quality initiatives.

KEY RESPONSIBILITIES

  • Lead and manage the Data QA team, providing technical direction, mentorship, and performance guidance
  • Lead QA and testing activities for data pipelines, ETL/ELT workflows, and data warehouse releases
  • Define and implement data quality standards, testing strategies, and quality gates
  • Develop and review test plans, test cases, and test results to ensure comprehensive test coverage
  • Partner with Data Engineering, Development, Product, and Business teams to identify, troubleshoot, and resolve data quality issues
  • Establish and improve QA processes, standards, and best practices to enhance data reliability and release quality
  • Monitor testing progress, defects, risks, dependencies, and overall release readiness
  • Drive continuous improvement in data QA processes, test automation, and testing efficiency
  • Ensure data releases meet established standards for quality, accuracy, completeness, consistency, and integrity
  • Identify opportunities to strengthen QA controls and reduce data-related production issues.

QUALIFICATIONS:

  • 6+ years of overall Quality Assurance (QA) experience
  • 3+ years of experience in Data QA / Data Quality testing
  • 2+ years of experience leading QA teams or QA initiatives
  • At least a Bachelor's Degree
  • Proven experience managing, mentoring, and providing technical guidance to QA engineers
  • Strong understanding of data pipelines, ETL/ELT processes, and data warehouses

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