1. REQUIREMENT TEMPLATE – Data-ETL Testing

No. of positions

16

Account Name

Allianz

Service Line

IQE

Must have skills - 2 skills which are non-negotiable

1. Strong SQL and Database Testing expertise with the ability to perform complex data validation and reconciliation.

2. Robust ETL Testing experience, including Source-to-Target Mapping validation, transformation testing, data integrity checks, and Data Warehouse concepts.

Desirable skills - 1 skill which is nice to have

Exposure to Big Data technologies such as Databricks, Hadoop, or Spark.

Infosys role

JL4 - 4

JL5 - 9

JL6 - 3

Desired experience range

5-18 Years

Location(s) where this position can work out of

Trivandrum, Pune, Bangalore, Chennai

Does this position require working from client office all or some days in the week? If yes pls provide details

No

Is remote working allowed

Any additional things to be checked

Responsibilities and JD in brief along with additional criteria to be considered (if any):

Role Summary The Data Tester is responsible for validating data accuracy, completeness, consistency, and integrity across source systems, ETL processes, databases, reports, and downstream applications. The role involves ensuring that business and technical data requirements are correctly implemented and that data transformations comply with business rules.

Key Responsibilities

1. Participate in all phases of the testing lifecycle, including requirement analysis, test planning, test execution, defect management, and reporting.

2. Validate data movement across source, staging, and target systems.

3. Perform Source-to-Target Mapping (STTM)



validation and ensure transformations are implemented correctly.

4. Develop and execute SQL queries for data verification, reconciliation, and integrity checks.

5. Validate ETL processes, data migration activities, and reporting outputs.

6. Perform data quality checks including completeness, accuracy, consistency, uniqueness, and validity.

7. Verify data lineage and ensure traceability between source and target systems.

8. Identify, analyze, and report data discrepancies and defects.

9. Collaborate with Business Analysts, Developers, ETL Engineers, and Data Architects to resolve data issues.

10. Create test cases, test scenarios, and test evidence for data validation activities.

11. Participate in Agile ceremonies and contribute from a quality engineering perspective.

Must-Have Skills

1. Advanced SQL & Database Testing

1. Strong SQL query writing and optimization skills.

2. Experience validating large datasets across multiple databases.

3. Expertise in joins, aggregations, subqueries, stored procedures, views, and data reconciliation.

2. ETL / Data Validation Testing

1. Strong understanding of ETL processes.

2. Experience validating Source-to-Target mappings.

3.



Knowledge of data transformation logic and business rule validation.

4. Data migration and reconciliation experience.

Additional Criteria to be Considered

Technical Skills

1. Experience with ETL tools such as:

2. Informatica

3. DataStage

Knowledge of Data Warehouse concepts:

1. Star Schema

2. Snowflake Schema

3. Fact & Dimension Modeling

4. Experience with NoSQL databases such as MongoDB.

5. API testing experience using Postman or similar tools.

6. Basic scripting knowledge (Python preferred).

7. Reporting and BI testing experience (Power BI, Tableau, Cognos).

Quality Engineering Expectations

1. Strong analytical and troubleshooting skills.

2. Ability to perform root cause analysis of complex data issues.

3. Understanding of data quality frameworks and governance principles.

4. Experience validating large-scale data transformations and migrations.

5. Knowledge of test automation approaches for data validation.

Domain Knowledge (Preferred)

1. Insurance domain experience.

Agile & Delivery Expectations

1. Experience working in Agile/Scrum teams.

2. Exposure to Jira, Azure DevOps, or similar ALM tools.

Soft Skills

1. Strong communication and stakeholder management skills.

2. Attention to detail and quality-focused mindset.

3. Ability to work independently and manage multiple priorities.

4. Strong collaboration and problem-solving abilities.

5. Good-to-Have Skills

6. MongoDB/Data Lake validation

7. Databricks/Spark

8. Cloud platforms (Azure, AWS, GCP)

9. Data lineage and metadata management tools

10. AI-assisted data testing tools

📌 ETL Testing (India)
🏢 Clifyx
📍 India