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.

Responsibilities

- Execute QA validation for bulk data products within the data exchange ecosystem
- Validate match and append processes and ensure correct deployment into data pipelines
- Provide QA support for data platform migrations, ensuring data integrity and functional correctness
- Verify data products and data fulfillment processes for accuracy and completeness
- 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
- Use and enhance quality check frameworks built with PySpark scripts to automate data validation
- Investigate defects through data analysis, identifying root causes in data pipelines or transformation logic
- Collaborate with engineering and data teams to triage issues, validate fixes, and confirm production readiness
- Contribute to test automation for data validation and testing to increase efficiency and coverage
- Communicate findings, risks, and test results clearly to stakeholders

Requirements

- 5+ years of experience in Data Quality Engineering
- Expertise in SQL, including complex joins across multiple tables and large datasets
- Hands-on experience with cloud data warehouses such as BigQuery, Redshift, or Synapse Analytics
- Working knowledge of cloud platform services across AWS, Azure, or GCP
- Understanding of data validation practices and automated data comparison techniques
- Background in data transformation, validation,



and mapping verification using specifications
- Capability to understand and work with PySpark-based quality frameworks
- Strong data analysis and debugging skills, with an ability to identify defects in data processing pipelines
- Excellent written and verbal communication skills
- Upper-Intermediate English proficiency (B2)

Nice to have

- Proficiency in Python or PySpark development
- Background in data engineering or data pipeline testing environments

We offer

- Connectivity Bonus (25,000 ARS are paid with a salary receipt at the end of each month as a non-wages concept).
- Medicina Prepaga (It covers the collaborator and direct family group).
- Paternity Leave (Two additional days are added to what is established by law, total of 4 days).
- Discounts card.
- English Training (English lessons, twice per week).
- Training Program (Access to multiple customized training plans according to the needs of each role within the company).
- Marriage bonus (The company doubles the allowance established by law that ANSES offers).
- Referral Program (Referral bonus is paid when the referral of a collaborator joins the Company).
- External Agreements and Discounts.
- Vacations: 14 calendar days a year

By applying to our role, you are agreeing that your personal data may be used as in set out in EPAM´s Privacy Notice and Policy.

EPAM is a leading general 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.

📌 Lead Data Quality Engineer (Argentina)
🏢 EPAM Systems
📍 Argentina