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Papigen

Posted 15 Oct 2026

QA & Data Validation Analyst

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Employment
Full time
Workplace
Remote
Posted
15 Oct 2026

About the role

Role Overview

We are looking for a QA & Data Validation Analyst with 5–7 years of experience in software testing, data validation, and reconciliation. The candidate will validate data pipelines, analytical datasets, Power BI reports, dashboards, APIs, and applications to ensure data accuracy, quality, and functional correctness for the portfolio.

Key Responsibilities

  • Develop test plans, test scenarios, test cases, validation scripts, and test data.

  • Perform functional, integration, regression, data-validation, and release testing.

  • Validate ETL/ELT pipelines, data transformations, calculations, aggregations, reports, dashboards, and APIs.

  • Perform source-to-target data reconciliation and identify missing, inconsistent, or inaccurate data.

  • Validate KPI calculations, dashboard outputs, and reporting controls.

  • Log, track, retest, and close defects in coordination with development and data teams.

  • Participate in root-cause analysis of recurring data-quality issues and production incidents.

  • Support UAT planning, execution, evidence collection, and business sign-off.

  • Perform pre-release and post-deployment validation.

  • Maintain test results, reconciliation reports, defect logs, and QA documentation.

Mandatory Skills & Experience

  • 5–7 years of QA / Software Testing / Data Validation experience

  • Strong data validation and reconciliation skills.

  • Functional, integration, regression, and UAT testing.

  • Experience testing ETL/ELT pipelines and data transformations.

  • SQL skills for data comparison, validation, and discrepancy analysis.

  • Experience validating reports, dashboards, analytical datasets, and calculations.

  • Defect tracking, retesting, and issue management.

  • Test documentation, validation evidence, and stakeholder communication.

Preferred Skills

  • Power BI report and dashboard validation.

  • Data warehouse, data lake, or analytical platform testing.

  • API testing and application testing.

  • Data-quality monitoring, governance, and data certification.

  • Experience with tools such as Jira, Azure DevOps, or similar defect-tracking platforms.

  • Financial services, portfolio, risk, or accounting data validation.

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