Are you passionate about data quality, analytics validation, and consumer insights? A fantastic career opportunity is now open for the role of Quality Assurance (QA Engineer) in Hyderabad with Mattel, one of the world’s most recognized entertainment and toy companies.
Known globally for creating iconic products and experiences, Mattel continues to expand its digital and analytics capabilities to better understand consumers, improve experiences, and drive innovation. This QA Engineer role is an exciting opportunity for professionals interested in working with consumer analytics platforms, data validation, ETL pipelines, and modern BI ecosystems.
If you have experience in SQL, data warehouse testing, analytics validation, and BI dashboard testing, this role can offer strong career growth and exposure to enterprise-scale consumer data systems.
📌 Job Overview
Position
Quality Assurance (QA Engineer)
Requisition Number
R236892
Location
Hyderabad, Telangana
Address
1804, 18th Floor, Gowra Palladium, Hyderabad – 500081
Job Category
Engineering
🚀 About the Role
The QA Engineer will play a critical role in validating consumer identity, behavioral, transactional, and analytics data across multiple layers of the enterprise data platform.
The selected candidate will work closely with:
- Data engineers
- Analytics teams
- BI developers
- Product stakeholders
The role focuses heavily on:
- Data quality validation
- ETL/ELT testing
- Consumer analytics testing
- Dashboard reconciliation
- KPI verification
- Data pipeline validation
This is an excellent opportunity for professionals who enjoy solving complex data problems and ensuring accurate analytics reporting.
💼 Key Responsibilities
1. Consumer Data Validation
One of the core responsibilities involves validating consumer-related data across source systems, transformation layers, and analytics datasets.
You will:
- Validate consumer identity and profile data
- Ensure transactional and behavioral data accuracy
- Verify consumer engagement datasets
- Test event-driven data ingestion processes
The role requires strong analytical thinking and attention to detail to identify inconsistencies in large datasets.
2. ETL/ELT Pipeline Testing
The selected candidate will perform extensive testing of data ingestion and transformation pipelines.
Responsibilities include:
- Validating ETL and ELT workflows
- Ensuring correct data transformations
- Verifying source-to-target mappings
- Detecting duplication and data loss issues
- Testing aggregation and rollup logic
Candidates should have experience working with modern data lake and warehouse architectures.
3. Dashboard & KPI Validation
The role also involves validating business intelligence dashboards and analytics reports.
You will:
- Reconcile KPIs displayed in Tableau and ThoughtSpot
- Validate dashboard metrics against warehouse tables
- Ensure analytics consistency across reporting systems
- Identify discrepancies in consumer reporting
Professionals with BI testing experience will find this aspect of the role especially relevant.
4. Data Quality & Reconciliation Testing
Data quality assurance is a major focus area for this position.
You will perform:
- Row-level testing
- Aggregate-level testing
- Trend-based validations
- Consumer record reconciliation
The goal is to identify:
- Mis-joins
- Incorrect rollups
- Data mismatches
- Transformation errors
- Missing records
Strong SQL expertise is essential for performing these validations effectively.
5. Collaboration with Engineering & Analytics Teams
The QA Engineer will work closely with cross-functional teams to resolve issues and improve data quality standards.
You will:
- Investigate consumer data issues
- Support root cause analysis
- Participate in Agile ceremonies
- Collaborate on analytics releases
- Improve validation frameworks
The role requires excellent communication skills to explain technical data issues to both engineering and business teams.
🛠 Required Skills & Qualifications
The organization is seeking candidates with strong expertise in data quality testing and analytics validation.
Experience Requirements
- 2–5 years of QA experience
- Experience in analytics, BI, or consumer data testing
- Exposure to enterprise data platforms
Technical Skills
SQL & Data Validation
Candidates should have:
- Strong SQL skills
- Experience validating consumer datasets
- Knowledge of BigQuery or similar platforms
- Ability to write reconciliation queries
ETL & Data Warehouse Testing
Experience with:
- Data pipelines
- ETL/ELT testing
- Data lake architectures
- Warehouse validation processes
BI & Dashboard Testing
Hands-on experience validating:
- Tableau dashboards
- ThoughtSpot analytics
- Consumer metrics
- Reporting KPIs
QA & Defect Management
Knowledge of:
- JIRA
- Test management processes
- Defect lifecycle management
- QA documentation
⭐ Preferred Qualifications
Additional preferred skills include:
- Experience with Looker or similar BI tools
- Understanding of consumer identity models
- Knowledge of event tracking systems
- Exposure to data quality automation frameworks
- Familiarity with CI/CD and Git
- Understanding of GDPR and CCPA compliance
- Experience with Postman or Pytest
These additional skills can help candidates stand out during the selection process.
📊 Technologies & Tools Involved
Professionals in this role may work with:
- SQL
- Google BigQuery
- Tableau
- ThoughtSpot
- Looker
- JIRA
- Git
- Postman
- Pytest
- CI/CD pipelines
This makes the role highly relevant for modern data engineering and analytics environments.
👨💻 Who Should Apply?
This opportunity is ideal for:
- Data QA Engineers
- ETL Test Engineers
- Analytics QA Professionals
- BI Testing Engineers
- SQL Test Analysts
- Tableau QA Specialists
- Consumer Data Validation Engineers
- Data Warehouse Testers
Professionals interested in analytics-driven quality assurance will find this role highly rewarding.
📩 How to Apply
Ready to take the next step in your career?
👉 Application Link: Click Here
🤝 Referral Tip
Want to improve your chances of getting noticed?
Connect with someone at Mattel and request a referral—it can significantly enhance your visibility in the hiring process.
