Database Tester

iSpace Software Solutions India Private Limited; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

iSpace Software Solutions India Private Limited seeks a data QA consultant to design and validate enterprise data pipelines in a cloud environment.

The role emphasizes SQL and Python-based automation, BigQuery validation, and CI/CD integration across Bronze-Silver data tiers, with governance focus for data quality and reliability.

Qualifications

• 5+ years of QA experience focused on data validation, ETL testing, data warehouse testing, or cloud data platform testing.
• Strong SQL skills for data validation, reconciliation, and analysis.
• Hands-on Python programming for test automation and data validation.

Responsibilities

• Design, develop, and execute test cases for enterprise data ingestion and transformation pipelines.
• Validate data movement from source systems into Bronze and Silver layers within BigQuery.
• Develop, maintain, and execute automated test scripts to validate data ingestion, transformation, and data quality processes.

Skills

Data QA

SQL

Python automation

Automation frameworks

Cloud data platforms

Tools

BigQuery

PyTest

Pandas

Job description

The ideal candidate will possess a blend of data testing, SQL, Python automation, and cloud data platform experience, with the ability to design both manual and automated validation solutions for enterprise data pipelines.

Key Responsibilities:

• Design, develop, and execute test cases for enterprise data ingestion and transformation pipelines.
• Validate data movement from source systems into Bronze and Silver layers within BigQuery.
• Perform source-to-target data validation and reconciliation testing.
• Verify data transformation logic, mappings, business rules, and data quality controls.
• Create and execute functional, integration, regression, and end-to-end test plans.
• Develop SQL queries to validate data completeness, accuracy, and consistency.
• Develop, maintain, and execute automated test scripts to validate data ingestion, transformation, and data quality processes.
• Leverage Python-based automation frameworks and utilities to improve testing efficiency, data validation, and regression testing coverage.
• Automate source-to-target data reconciliation and validation activities for large datasets within GCP and BigQuery environments.
• Collaborate with engineering teams to integrate automated testing into CI/CD pipelines and release processes.
• Identify, document, and track defects through resolution.
• Collaborate closely with developers, architects, product owners, and business stakeholders.
• Participate in Agile ceremonies including sprint planning, backlog refinement, and daily stand-ups.
• Support production validation activities and post-release verification.
• Provide test evidence and documentation to support data governance and compliance requirements.
• Ensure enterprise data quality standards are maintained across onboarding initiatives.

Required Skills and Expertise:

• 5+ years of QA experience focused on data validation, ETL testing, data warehouse testing, or cloud data platform testing.
• Strong SQL skills with the ability to write complex queries for data validation, reconciliation, and data analysis.
• Hands-on experience with Python programming for test automation, data validation, scripting, or process automation.
• Experience developing and maintaining automated test frameworks, automated validation scripts, or test automation solutions.
• Experience testing cloud-based data platforms and data pipelines.
• Experience validating large datasets and complex data transformations.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Experience with defect tracking and test management tools.
• Familiarity with Agile/Scrum methodologies.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent verbal and written communication skills.
• Ability to work effectively with distributed global teams.

Highly Preferred Skills and Expertise:

• Experience with Google Cloud Platform (GCP).
• Experience validating data within BigQuery environments.
• Familiarity with Dataflow and cloud-based data processing frameworks.
• Experience testing data ingestion and transformation pipelines.
• Experience using Python libraries and frameworks such as PyTest, Pandas, NumPy, or custom automation frameworks.
• Experience building automation solutions for data reconciliation, ETL validation, API testing, or regression testing.
• Experience with Java-based data processing applications.
• Understanding of Medallion Architecture (Bronze, Silver, Gold).
• Experience supporting enterprise data modernization initiatives.
• Exposure to CI/CD pipelines and Git-based source control.
• Knowledge of data governance, data quality frameworks, and cloud security best practices.
• Exposure to analytics, AI, or machine learning data platforms.

What Success Looks Like:

The successful consultant will help ensure that enterprise data entering our client's Enterprise Data Platform is accurate, reliable, and ready for analytics and AI consumption by:

• Validating data onboarding processes from source systems into BigQuery.
• Ensuring Bronze and Silver layer transformations meet business and technical requirements.
• Developing automated validation solutions using Python to improve testing efficiency and data quality coverage.
• Identifying and resolving data quality issues before production deployment.
• Supporting the delivery of scalable, trusted, and governed enterprise data assets.
• Collaborating effectively with both offshore and U.S.-based engineering teams.
• Contributing to the continuous improvement of QA automation, testing processes, and data quality standards across the platform.