Senior QA Engineer (Automation, Data & ETL Testing)

Job Description – Senior QA Engineer (Automation, Data & ETL Testing)

Position: Senior Automation Engineer – Data & ETL Testing Experience: 5–8 Years

About the Role

Infoya is looking for an experienced Senior Automation Engineer with strong expertise in test automation , database testing, ETL validation, and data pipeline testing. The ideal candidate will have hands-on experience working with cloud-based data platforms, complex data architectures, and business intelligence solutions.

The candidate will be responsible for ensuring data accuracy, integrity, consistency, reliability, and performance across enterprise data pipelines and analytical platforms.

Key Responsibilities

1. Test Automation (Mandatory)

• Design, develop, and maintain

automated testing frameworks for database, ETL, and data pipeline validation.

• Develop reusable automated test

scripts using Python, SQL, or equivalent technologies.

• Automate source-to-target

reconciliation, data quality checks, schema validation, and regression testing.

• Integrate automated tests into

CI/CD pipelines.

• Improve test coverage, execution

efficiency, and overall QA productivity through automation

2. Database Testing & Data Validation

• Design and execute comprehensive

database testing strategies for complex enterprise applications.

• Perform advanced SQL-based

validation, including complex joins, aggregations, stored procedures, and data reconciliation.

• Validate data integrity,

completeness, accuracy, and consistency across source and target systems.

• Conduct backend testing using

PostgreSQL and StarRocks.

• Identify data quality issues,

transformation defects, and performance bottlenecks.

3. ETL & Data Pipeline Testing

• Validate end-to-end ETL/ELT

workflows, including data extraction, transformation, loading, and reconciliation.

• Test batch and streaming data

pipelines for accuracy, completeness, and reliability.

• Validate transformation rules,

data mappings, business logic, and aggregation calculations.

• Perform incremental load, full

load, duplicate detection, and data consistency testing.

• Verify error handling, recovery

mechanisms, and data pipeline dependencies.

4. Cloud & Data Platform Testing

• Work with Google Cloud Platform

(GCP) to validate cloud-based data processing and storage solutions.

• Perform data validation across

PostgreSQL, StarRocks, and other enterprise data platforms.

• Test data ingestion, processing,

transformation, and integration workflows.

• Collaborate with Data Engineers,

Cloud Engineers, and Developers to troubleshoot data-related issues.

5. Business Intelligence & Reporting Validation

• Validate Tableau dashboards,

reports, KPIs, and analytical outputs.

• Reconcile dashboard data against

underlying databases and source systems.

• Verify business rules, filters,

aggregations, calculations, and reporting accuracy.

• Ensure consistency between

analytical data layers and business reporting.

6. Performance Testing (Good to have knowledge)

• Perform database query

performance testing and optimization validation.

• Evaluate ETL pipeline throughput,

processing latency, and scalability.

• Support load, stress, and volume

testing for data-intensive applications.

• Identify performance bottlenecks

and collaborate with engineering teams on improvements.

Required Qualifications

• 5-8 years of experience in

Software Quality Engineering, with significant hands-on experience in database and ETL testing.

• Strong experience in developing

automated test scripts and reusable testing frameworks.

• Excellent SQL skills with

expertise in complex queries, joins, aggregations, and data validation.

• Practical experience with

PostgreSQL, StarRocks, Tableau, and GCP.

• Knowledge with GCP services such

as BigQuery, Cloud Storage, Dataflow, or Cloud Composer.

• Proven experience validating

end-to-end data pipelines and ETL/ELT processes.

• Strong understanding of data

warehousing concepts, dimensional modeling, and data quality principles.

• Experience working in Agile

delivery environments.

• Strong analytical,

troubleshooting, communication, and stakeholder collaboration skills.

Preferred / Good-to-Have Skills

• Performance testing experience

for databases and large-scale data pipelines.

• Familiarity with PyTest, Great

Expectations, dbt testing, or similar data quality automation tools.

• Experience testing large-volume

datasets and near-real-time data processing.

• Exposure to DevOps, CI/CD, and

cloud-native testing practices.

Expected Outcomes

The successful candidate will:

• Establish robust automated

testing coverage across critical data pipelines.

• Improve data quality and reduce

production data defects.

• Strengthen end-to-end validation

across source systems, databases, and Tableau reporting.

• Accelerate regression testing

through automation and reusable frameworks.

• Collaborate proactively with

engineering teams to improve the reliability and scalability of enterprise data platforms.

Ideal Candidate: A technically strong, hands-on Senior QA Engineer who combines advanced SQL and database testing expertise with automation-first thinking, ETL/data pipeline validation experience, and practical exposure to modern cloud data platforms.