Description

You will own data quality strategies, ETL testing, and AWS pipeline monitoring to ensure data accuracy and reliability.

This role is on-site.

Responsibilities

• Design and execute ETL test cases, validating data transformations, accuracy, and end-to-end pipeline performance.
• Monitor and optimize AWS data pipelines using Glue, S3, Athena, MSK, SQS, Lambda, and Step Functions.
• Develop Python scripts to automate data quality checks and validation processes.
• Collaborate with data engineers and stakeholders to resolve data quality issues and understand data flows.
• Maintain detailed documentation of testing procedures, results, and quality metrics.

Required Skills

• 5+ years of experience in data quality engineering, data testing, or related fields.
• Strong hands-on experience with ETL testing and data validation techniques.
• Proficiency in SQL and Python.
• Experience with AWS data services: Glue, S3, Athena, MSK, SQS, Lambda, Step Functions.
• Experience validating data in Power BI reports, including data models and report logic.
• Familiarity with test management tools such as Azure DevOps, Zephyr, or equivalent.
• Experience working in Agile environments (Scrum/Kanban).

Preferred Skills

• Exposure to data governance principles or data observability tools.
• Proficiency in other OOP languages like Java, C, or C++.

Key Skills

Education

Bachelor's degree