Quality Assurance Engineer – Google Cloud

Are you a high-performing QA expert ready to help shape the future of global marketing technology? Our  Global Campaign Tracking (GCT)  team, part of the Enterprise Personalization Portfolio, is looking for a skilled  Quality Assurance Engineer  to deliver next-generation capabilities.
In this role, you will be the subject matter expert driving automation and quality strategies for large-scale data processing pipelines and cloud migrations.

Mandatory

Skills & Qualifications

Please note:

We are looking for candidates who meet the following specific technical requirements. Please apply only if you possess these matching skills.

Experience:

6–9 years  of hands-on software testing experience, including extensive knowledge of automated testing and architecture.
Big Data & GCP Expertise:  Deep expertise in developing test cases for   Big Query   ,    Data Proc   ,    Hive   , and    Spark   .
Programming for QA:  Proficiency in writing test scripts  using    PySpark   ,    SQL   , and    Scala   .
Testing Frameworks:  Expert knowledge of Test Automation Design Patterns and frameworks such as   TDD     (Test Driven Development) and   BDD     (Behavior Driven Development).
Performance Testing:  Hands-on experience with tools  like    JMeter   ,    pytest   , or similar  performance and load testing utilities.
Cloud & Distributed Systems:  Proven experience testing and debugging resilient distributed systems using   Big Data Clusters    and    Google Cloud Platform (GCP)   .
Agile Proficiency:  Experience working within  Agile methodologies  and using industry-standard tools for defect tracking and source code management.

Key Responsibilities
Pipeline Validation:  Testing and quality assurance of large-scale data pipelines using PySpark and SQL.
Migration Testing:  Writing scripts to validate the migration of Hadoop/Spark/Hive workloads to Google Cloud.
Strategy & Automation:  Driving the automation strategy at the application and portfolio levels to ensure the highest quality code.
Environment Management:  Setting up and maintaining test data and environments across development, staging, and production.
Backlog Review:  Reviewing user stories and requirements for functional completeness, performance, reliability, and security.

Bonus Skills
Experience testing  Machine Learning  or data mining models.
Familiarity with building and adopting entirely new test frameworks.

Location:

Chennai

Note to Applicants:
We are looking for a specific technical match for this high-energy team.  Please apply only if you meet the mandatory skill requirements listed above.