Lead Data Quality Engineer - Validation & Automation

EPAM Systems; Chile; Hybrid; CLP 60,000,000 - 90,000,000; Full time

Benefits offered by this job

Medical coverage

Lunch allowance

Internet & electricity allowance

Holiday bonus

Learning culture

Job summary

EPAM Systems is 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 and support migrations and deployments within modern data ecosystems.

You will work with PySpark-based quality frameworks and collaborate with data teams to triage issues, validate fixes, and ensure production readiness. Strong English communication and leadership are expected.

Qualifications

• 5+ years of experience in Data Quality Engineering.
• Expertise in SQL with complex joins across large datasets.
• Hands-on experience with cloud data warehouses (BigQuery/Redshift/Synapse).
• Working knowledge of cloud services across AWS, Azure, or GCP.
• Understanding of data validation practices and automated comparisons.
• Background in data transformation and mapping verification.

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 correctness.
• Verify data products and data fulfillment processes for accuracy and completeness.
• Perform data validation and comparisons across systems and mappings against specifications.
• Use PySpark-based quality frameworks to automate data validation.

Skills

Data Quality

SQL

Cloud data warehouses

PySpark

Data validation

Education

Bachelor's degree or equivalent

Tools

BigQuery

Redshift

Synapse Analytics

AWS

Azure

GCP

Job description

EPAM Systems is 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 and support migrations and deployments within modern data ecosystems.

You will work with PySpark-based quality frameworks and collaborate with data teams to triage issues, validate fixes, and ensure production readiness. Strong English communication and leadership are expected.