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Virtusa

Data QA Specialist ( Remote from Poland)

Virtusa

IT Services and IT Consulting · 10,001+ employees

20 h ago
Remote qa Mid (2-5 yrs) Full-time
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About the role

You will design and execute end-to-end test strategies for data pipelines and perform comprehensive data warehouse testing in Snowflake. Additionally, you will drive data reconciliation processes and ensure the accuracy and reliability of the enterprise data platform.

What they look for

ETL Testing Data Pipeline Validation Data Warehouse QA Snowflake SQL Data Reconciliation Data Architecture Dimensional Modeling Star Schema Snowflake Schema JSON Parquet CSV XML Data Auditing

Requirements

Candidates must have 4+ years of experience in ETL testing and data warehouse QA with strong proficiency in SQL. A clear understanding of data architecture, dimensional modeling, and various data file formats is also required.

Full description

This is a remote position.

We are seeking a detail-oriented and analytical Data QA Engineer to join our data engineering team. In this role, you will play a vital part in ensuring the accuracy, consistency, and reliability of our enterprise data platform. You will design, develop, and execute end-to-end test strategies for data pipelines, perform comprehensive data warehouse testing in Snowflake, and drive data reconciliation processes across disparate systems.

Requirements

  • 4+ years of dedicated experience in ETL testing, data pipeline validation, and Data Warehouse QA.
  • Strong hands-on experience querying, testing, and navigating a Snowflake data warehouse environment.
  • Exceptional SQL skills, including expertise in complex joins, window functions, CTEs, subqueries, and set operations to compare large datasets efficiently.
  • Proven experience designing data reconciliation workflows, source-to-target validation scripts, and data auditing routines.
  • Clear understanding of data architecture, dimensional modeling (Star Schema, Snowflake Schema), and data file formats (JSON, Parquet, CSV, XML).
  • Excellent problem-solving skills with high attention to detail when analyzing large, complex datasets.
  • Communicative English

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