We are seeking a Lead Data Quality Engineer to drive rigorous data validation, SQL-based testing, and quality automation across cloud data environments. You will verify complex transformations, ensure consistency across multiple systems, and support migration and deployment work within modern data ecosystems. Join a distributed team focused on trustworthy datasets and apply today.
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Responsibilities
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Execute QA validation for bulk data products within the data exchange ecosystem
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Validate match and append processes and ensure correct deployment into data pipelines
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Provide QA support for data platform migrations, ensuring data integrity and functional correctness
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Verify data products and data fulfillment processes for accuracy and completeness
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Perform data validation and comparisons across systems, including source input files to cloud data warehouse tables, table-to-table checks, and confirmation of data mappings and transformations against specifications
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Use and enhance quality check frameworks built with PySpark scripts to automate data validation
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Investigate defects through data analysis, identifying root causes in data pipelines or transformation logic
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Collaborate with engineering and data teams to triage issues, validate fixes, and confirm production readiness
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Contribute to test automation for data validation and testing to increase efficiency and coverage
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Communicate findings, risks, and test results clearly to stakeholders
Requirements
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5+ years of experience in Data Quality Engineering
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Expertise in SQL, including complex joins across multiple tables and large datasets
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Hands-on experience with cloud data warehouses such as BigQuery, Redshift, or Synapse Analytics
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Working knowledge of cloud platform services across AWS, Azure, or GCP
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Understanding of data validation practices and automated data comparison techniques
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Background in data transformation, validation, and mapping verification using specifications
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Capability to understand and work with PySpark-based quality frameworks
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Strong data analysis and debugging skills, with an ability to identify defects in data processing pipelines
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Excellent written and verbal communication skills
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Upper-Intermediate English proficiency (B2)
Nice to have
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Proficiency in Python or PySpark development
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Background in data engineering or data pipeline testing environments
We offer
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Connectivity Bonus (25,000 ARS are paid with a salary receipt at the end of each month as a non-wages concept).
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Medicina Prepaga (It covers the collaborator and direct family group).
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Paternity Leave (Two additional days are added to what is established by law, total of 4 days).
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Discounts card.
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English Training (English lessons, twice per week).
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Training Program (Access to multiple customized training plans according to the needs of each role within the company).
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Marriage bonus (The company doubles the allowance established by law that ANSES offers).
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Referral Program (Referral bonus is paid when the referral of a collaborator joins the Company).
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External Agreements and Discounts.
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Vacations: 14 calendar days a year
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