Description

You will own the quality assurance and automated testing strategy for large-scale enterprise data systems and ETL pipelines.

This role is on-site.

Responsibilities

• Design and execute detailed test strategies, test cases, and scripts to validate data accuracy and integrity within ETL pipelines.
• Develop and maintain automated test frameworks for data applications, APIs, and integration systems.
• Collaborate with data engineers to monitor data completeness and validate transformations across data platforms.
• Conduct performance and load testing to evaluate the scalability and stability of large-scale data systems.
• Mentor junior quality engineers on technical skills and quality engineering best practices.

Required Skills

• 10+ years of professional experience in software quality engineering.
• Expertise in ETL processes, data warehousing, and data lakes.
• Proficiency in SQL and Python for test automation and data validation.
• Hands-on experience with Pytest and ETL automation tools such as Airflow or DBT.
• Experience testing data pipelines and event-driven streaming platforms like Kafka.
• Strong knowledge of Azure Data Factory and Azure Synapse.
• Experience working within Agile and Scrum frameworks.
• Ability to perform performance testing using tools like JMeter or LoadRunner.

Preferred Skills

• Experience with Microsoft Fabric.

Key Skills

Education

Any Graduate