Senior Test Lead
HCLTech
Senior Test Lead
About this role
Job Summary
Job Title : Data QA Engineer (GCP / BigQuery)
Job Summary
We are seeking a Data QA Engineer to validate the correctness of data engineering solutions built on Google Cloud Platform (GCP). The role is focused on testing ETL/ELT pipelines, data transformation logic, and data processing workflows by comparing outputs against expected reference datasets and verifying that implemented business rules produce the expected results.
The role is strictly focused on quality assurance and test automation for data engineering deliverables. It does not involve data cleansing, data quality remediation, or production data support.
Key Responsibilities
- Validate ETL/ELT pipelines, transformation logic, and data processing workflows.
- Develop SQL-based test cases and reconciliation queries using BigQuery.
- Compare outputs from new pipelines and transformations against trusted reference datasets.
- Perform source-to-target validation, regression testing, and functional testing of data engineering artifacts.
- Design, develop, and maintain automated test scripts and reusable validation frameworks using Python.
- Execute test plans, record test results, and report defects with sufficient evidence for resolution by development teams.
- Collaborate with Data Engineers to clarify requirements, validate fixes, and ensure successful delivery.
- Contribute to the continuous improvement of QA processes, automation frameworks, and testing standards.
Required Skills
- Strong SQL expertise with hands-on experience in BigQuery.
- Strong Python programming skills for test automation.
- Experience with Google Cloud Platform (GCP), including BigQuery and GCS; exposure to Cloud Composer, Dataflow, or Dataproc is desirable.
- Strong understanding of ETL/ELT processes, data transformations, and data warehousing concepts.
- Familiarity with Backend Kafka and API
- Experience in data validation, reconciliation testing, and regression testing.
- Familiarity with Git, CI/CD pipelines, and automated testing frameworks.
Experience
- 6 – 10 years of experience in Data QA, ETL Testing, or Data Test Automation.
- Experience testing cloud-based data engineering solutions, preferably on GCP.
Key Competencies
- SQL and analytical skills
- Test automation using Python
- Defect identification and reporting
- Problem-solving
- Collaboration and communication
- Quality assurance mindset
Regards,
Key Responsibilities
Job Title : Data QA Engineer (GCP / BigQuery)
Job Summary
We are seeking a Data QA Engineer to validate the correctness of data engineering solutions built on Google Cloud Platform (GCP). The role is focused on testing ETL/ELT pipelines, data transformation logic, and data processing workflows by comparing outputs against expected reference datasets and verifying that implemented business rules produce the expected results.
The role is strictly focused on quality assurance and test automation for data engineering deliverables. It does not involve data cleansing, data quality remediation, or production data support.
Key Responsibilities
- Validate ETL/ELT pipelines, transformation logic, and data processing workflows.
- Develop SQL-based test cases and reconciliation queries using BigQuery.
- Compare outputs from new pipelines and transformations against trusted reference datasets.
- Perform source-to-target validation, regression testing, and functional testing of data engineering artifacts.
- Design, develop, and maintain automated test scripts and reusable validation frameworks using Python.
- Execute test plans, record test results, and report defects with sufficient evidence for resolution by development teams.
- Collaborate with Data Engineers to clarify requirements, validate fixes, and ensure successful delivery.
- Contribute to the continuous improvement of QA processes, automation frameworks, and testing standards.
Required Skills
- Strong SQL expertise with hands-on experience in BigQuery.
- Strong Python programming skills for test automation.
- Experience with Google Cloud Platform (GCP), including BigQuery and GCS; exposure to Cloud Composer, Dataflow, or Dataproc is desirable.
- Strong understanding of ETL/ELT processes, data transformations, and data warehousing concepts.
- Familiarity with Backend Kafka and API
- Experience in data validation, reconciliation testing, and regression testing.
- Familiarity with Git, CI/CD pipelines, and automated testing frameworks.
Experience
- 6 – 10 years of experience in Data QA, ETL Testing, or Data Test Automation.
- Experience testing cloud-based data engineering solutions, preferably on GCP.
Key Competencies
- SQL and analytical skills
- Test automation using Python
- Defect identification and reporting
- Problem-solving
- Collaboration and communication
- Quality assurance mindset
Regards,
Skill Requirements
Key Competencies
- SQL and analytical skills
- Test automation using Python
- Defect identification and reporting
- Problem-solving
- Collaboration and communication
- Quality assurance mindset
Other Requirements
Frequently Asked Questions
Is the salary disclosed for the Senior Test Lead position at HCLTech?
The salary for this Senior Test Lead role at HCLTech is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Senior Test Lead position at HCLTech located?
This Senior Test Lead role at HCLTech is based in Hyderabad, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
How do I apply for the Senior Test Lead position at HCLTech?
Click the "Apply Now" button on this page. You will be redirected to HCLTech's official application portal hosted on successfactors where you can submit your application directly.
When was the Senior Test Lead job at HCLTech posted?
This Senior Test Lead position at HCLTech was posted on Sep 21, 2026. Apply as soon as possible — early applications are often reviewed first.
Senior Test Lead
HCLTech
You'll be redirected to HCLTech's official application page on successfactors.