Lead Data Quality Engineer: Data Validation & Automation

EPAM Systems; Argentina; Híbrido; ARS 1.800.000 - 3.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Connectivity Bonus

Medicina Prepaga

Paternity Leave

Discount Card

English Training

Training Program

Marriage Bonus

Referral Program

External Discounts

Vacation Days

Descripción de la vacante

EPAM Systems seeks a Lead Data Quality Engineer to drive data validation, SQL testing, and quality automation across cloud data environments.

You will verify transformations, ensure data integrity across systems, and support migrations and deployments within modern data ecosystems, collaborating with distributed teams.

This role focuses on building PySpark-based checks, debugging data pipelines, and communicating risks and results to stakeholders.

Formación

• 5+ years of experience in Data Quality Engineering
• Expertise in SQL, including complex joins across 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)

Responsabilidades

• 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

Conocimientos

SQL

Data validation

PySpark

Cloud data warehouses

Data transformation

Educación

Bachelor's degree in a relevant field

Herramientas

BigQuery

Redshift

Synapse Analytics

Descripción del empleo

EPAM Systems seeks a Lead Data Quality Engineer to drive data validation, SQL testing, and quality automation across cloud data environments.

You will verify transformations, ensure data integrity across systems, and support migrations and deployments within modern data ecosystems, collaborating with distributed teams.

This role focuses on building PySpark-based checks, debugging data pipelines, and communicating risks and results to stakeholders.