Quality Assurance Engineer

EXL

QA Engineer with experience in data platform validation for data pipelines and lakehouse architecture on AWS and Snowflake. Collaborating with engineers to guarantee data quality under rigorous standards.

Posted 6/3/2026full-time🇮🇳 IndiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAWSETLPySparkSQL

About the role

Key responsibilities & impact

Design and execute test strategies for data pipelines built using PySpark and orchestrated via Airflow.
Validate data ingestion, transformation, and storage in S3-based lakehouse (Iceberg tables).
Perform data reconciliation between source systems, lakehouse, and Snowflake business layer.
Develop automated test frameworks for large-scale data validation.
Ensure data quality, completeness, consistency, and performance across pipelines.
Collaborate with data engineers and stewards to enforce data quality rules and governance standards.
Identify, track, and resolve defects in data workflows and reporting layers.

Requirements

What you’ll need

5+ years of QA experience with a focus on data platforms or ETL testing.
Strong SQL skills and experience validating large datasets.
Experience with PySpark-based data validation or big data testing tools.
Familiarity with Airflow workflows and AWS data ecosystem (S3).
Understanding of Snowflake data validation and performance testing.
Experience with test automation frameworks.

Benefits

Comp & perks

Health insurance
Paid time off
Professional development opportunities

ATS Keywords

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Hard Skills & Tools

PySparkSQLETL testingdata validationtest automation frameworksdata reconciliationperformance testingdata qualitybig data testing toolsdata ingestion

Soft Skills

collaborationproblem-solvingattention to detailcommunicationorganizational skills