If you are interested in Data Engineering, ETL Testing, SQL Validation, Business Intelligence, and Data Quality Assurance, this Data Warehouse QA Tester opportunity at Zensar Technologies can be a strong career opportunity.
The company is hiring Data Warehouse QA Testers for its Pune office and is looking for professionals with strong SQL expertise, ETL testing experience, data warehousing knowledge, and analytical problem-solving skills.
This role is ideal for candidates who want to work with enterprise data platforms, large datasets, BI systems, cloud data technologies, and modern QA methodologies.
Job Details
Position Name
Data Warehouse QA Tester
Company Name
Zensar Technologies
Job Location
Pune
Experience Required
1 Year
Work Mode
Work from Anywhere Available
Job Shift
Day Shift
Industry Domain
Data Engineering & Analytics
About Zensar Technologies
Zensar Technologies is a global technology and digital solutions company that delivers enterprise-scale IT services, cloud solutions, AI-driven systems, digital engineering, and analytics solutions to leading businesses worldwide.
The company is part of the RPG Group, a multinational business group with a strong global presence. Zensar operates across more than 30 locations worldwide and serves clients across industries such as:
- Banking & Financial Services
- Healthcare
- Manufacturing
- Insurance
- Public Sector
- Telecommunications
The organization focuses heavily on digital transformation, cloud infrastructure, AI engineering, cybersecurity, data analytics, and enterprise modernization.
Description
Zensar is hiring Data Warehouse QA Testers responsible for validating the accuracy, completeness, reliability, and quality of enterprise data warehouse systems and ETL pipelines.
The role involves ETL testing, SQL validation, data reconciliation, regression testing, reporting verification, defect management, and collaboration with data engineers and BI teams.
Candidates should have strong SQL skills, understanding of data warehousing concepts, ETL testing expertise, and knowledge of modern cloud and big data technologies.
Roles and Responsibilities
Test Planning & Strategy
The selected candidate will:
- Create test plans and test cases
- Develop testing strategies for data warehouse systems
- Define acceptance criteria
- Validate data quality standards
This includes testing data completeness, accuracy, transformation logic, and referential integrity.
ETL Testing & Data Validation
Candidates will perform:
- Source-to-target data validation
- Transformation rule verification
- Workflow dependency testing
- Regression testing
- System integration testing
- User Acceptance Testing (UAT) support
The role also requires validating data movement across:
- Staging Layer
- Integration Layer
- Data Warehouse
- Data Marts
SQL Querying & Data Profiling
Data Quality=Accuracy+Completeness+ConsistencyData\ Quality=Accuracy+Completeness+Consistency
Strong SQL expertise is one of the most critical requirements for this role.
Candidates will:
- Write complex SQL queries
- Perform data reconciliation
- Validate large datasets
- Analyze data inconsistencies
- Conduct data profiling activities
Defect Management
The QA Tester will:
- Identify and document defects
- Work with Jira/Azure DevOps/Rally
- Collaborate with developers and data engineers
- Retest fixes and monitor issue resolution
Collaboration & Documentation
The role requires working closely with:
- Data Engineers
- BI Developers
- Data Architects
- Business Analysts
- QA Teams
Candidates must also maintain:
- Testing documentation
- Validation reports
- QA guidelines
- Mapping verification documents
Required Skills and Their Importance
SQL Skills
Strong SQL expertise is mandatory.
Why it matters:
- SQL is essential for validating warehouse data
- Helps perform reconciliation and profiling
- Enables testing of large enterprise datasets
Key concepts include:
- Complex joins
- Aggregations
- Window functions
- Data profiling
Data Warehousing Concepts
Candidates should understand:
- Fact tables
- Dimension tables
- Star schemas
- Snowflake schemas
- Slowly Changing Dimensions (SCDs)
Why it matters:
- These are core building blocks of enterprise data warehouses
- Proper validation ensures accurate reporting and analytics
ETL Testing
Experience with ETL tools such as:
- Informatica
- SSIS
- Azure Data Factory
- DataStage
- Snowflake
- Databricks
is important.
Why it matters:
- ETL pipelines move business-critical data
- QA ensures transformation accuracy
- Prevents reporting inconsistencies
BI & Reporting Tools
Knowledge of:
- Power BI
- Tableau
- Looker
- MicroStrategy
is beneficial.
Why it matters:
- Business decisions rely on reporting accuracy
- QA validation improves dashboard reliability
Cloud Data Platforms
Experience with:
- Azure
- AWS
- GCP
is preferred.
Why it matters:
- Modern data warehouses are cloud-based
- Cloud expertise improves scalability understanding
Big Data Technologies
Exposure to:
- Spark
- Hive
- Databricks
is an advantage.
Why it matters:
- Enterprise datasets are growing rapidly
- Big data technologies improve distributed processing capabilities
Python & Automation
Knowledge of Python scripting is preferred.
Why it matters:
- Automation improves testing efficiency
- Reduces repetitive manual testing
- Supports CI/CD integration
QA Methodologies & Defect Tracking
Candidates should understand:
- QA lifecycle
- Test management
- Defect tracking tools
Why it matters:
- Structured QA processes improve software quality
- Defect management improves collaboration and issue resolution
Soft Skills Required
Attention to Detail
Why it matters:
- Data quality depends on accuracy
- Small validation errors can impact business reports
Communication Skills
Why it matters:
- QA teams work with multiple stakeholders
- Clear documentation improves collaboration
Problem-Solving Ability
Why it matters:
- Data inconsistencies require analytical thinking
- Faster issue resolution improves delivery quality
Team Collaboration
Why it matters:
- Enterprise projects involve cross-functional coordination
- Collaboration improves delivery efficiency
Why This Opportunity is Valuable
This role provides exposure to:
- Enterprise data warehouse systems
- ETL testing frameworks
- Cloud data platforms
- Business Intelligence systems
- Big data technologies
- QA automation concepts
- Enterprise analytics environments
Professionals can strengthen:
- SQL expertise
- Data engineering knowledge
- QA methodologies
- Reporting validation skills
- Automation capabilities
Career Growth Opportunities
Working at Zensar Technologies can help professionals grow toward roles such as:
- ETL QA Engineer
- Data Quality Analyst
- BI QA Engineer
- Data Engineer
- QA Automation Engineer
- Analytics QA Specialist
- Data Validation Consultant
The company provides opportunities to work on enterprise digital transformation and analytics projects.
Work Culture at Zensar
Zensar promotes:
- Innovation-driven engineering
- Continuous learning
- Team collaboration
- Employee growth
- Diversity and inclusion
- Client-focused delivery
The company encourages professionals to:
- Improve technical expertise
- Learn modern technologies
- Collaborate globally
- Contribute innovative ideas
Zensar’s engineering culture supports both technical growth and professional development.
Final Thoughts
The Data Warehouse QA Tester role at Zensar Technologies is an excellent opportunity for professionals interested in SQL validation, ETL testing, data quality engineering, and enterprise analytics systems.
Candidates with strong SQL skills, data warehousing knowledge, ETL testing experience, and analytical thinking abilities can significantly enhance their careers through this opportunity.
This role is especially suitable for professionals who enjoy working with enterprise data systems, validation processes, reporting accuracy, and cloud-based analytics environments.
Apply Here: Visit Link
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