Appzlogic Mobility - Senior ETL Quality Assurance Engineer

Detailed Job Description :

Role : ETL DBA QA Engineer (8+ Years Experience)

The ideal candidate should possess strong analytical and troubleshooting skills, extensive experience validating complex ETL workflows, database objects, stored procedures, triggers, and data migration processes.

The candidate will work closely with Business Analysts, Data Engineers, ETL Developers, DBAs, and Product Owners to ensure high-quality data across enterprise data platforms while maintaining data integrity, accuracy, and performance.

Key Responsibilities :

1. ETL Testing :

- Validate end-to-end ETL/ELT workflows across multiple environments.

- Perform Source-to-Target Mapping (STM) validation.

- Verify data extraction, transformation, and loading processes.

- Validate Full Load, Incremental Load, Delta Load, and CDC (Change Data Capture).

- Perform Data Reconciliation between source and target systems.

- Validate business transformation rules.

- Test error handling, exception management, and reject records.

- Execute Batch Testing and Scheduler validation.

- Validate complex ETL pipelines and workflow dependencies.

- Perform Regression, Functional, Integration, and System Testing for ETL applications.

2. Database Testing :

- Validate database tables, views, indexes, sequences, synonyms, constraints, and relationships.

- Test complex SQL queries involving : 1. Joins 2. Subqueries 3. CTEs 4. Window Functions 5. Aggregations 6. Set Operators.

- Validate : 1. Stored Procedures 2. Functions 3. Packages 4. Triggers 5. Cursors.

- Verify database transactions and rollback mechanisms.

- Validate Referential Integrity.

- Perform Schema Validation.

- Validate Data Migration and Database Upgrade Testing.

- Execute Data Integrity Testing.

3. Data Warehouse Testing :

- Validate Star Schema and Snowflake Schema.

- Test Fact and Dimension tables.

- Validate Slowly Changing Dimensions (SCD Type 1, 2, and 3).

- Verify Surrogate Keys and Natural Keys.

- Perform Historical Data Validation.

- Validate Aggregate Tables.

- Test Data Mart implementation.

- Validate Data Warehouse loading processes.

4. DBA QA Responsibilities :

- Validate database deployment activities.

- Verify database object creation scripts.

- Perform Database Health Validation after deployments.

- Validate backup and recovery procedures.

- Verify permissions, roles, and user access.

- Validate database configuration changes.

- Test schema migration scripts.

- Validate release deployment scripts.

- Verify production database changes.

5. SQL Validation :

- Write complex SQL queries for : 1. Data Validation 2. Reconciliation 3. Duplicate Detection 4. Missing Data Validation 5. Data Quality Checks 6. Referential Integrity Validation.

- Perform row count validation.

- Perform aggregate validation.

- Validate null values.

- Validate duplicate records.

- Compare source and target datasets.

6. Performance Testing :

- Validate ETL execution performance.

- Analyze long-running SQL queries.

- Validate execution plans.

- Perform database performance validation.

- Test indexing strategies.

- Validate query optimization.

- Monitor ETL batch execution time.

7. Defect Management :

- Identify root causes of data defects.

- Log defects with complete evidence.

- Work closely with ETL Developers and DBAs for issue resolution.

- Perform defect retesting.

- Conduct impact analysis.

- Maintain defect metrics and reporting.

8. Test Planning :

- Review Business Requirement Documents (BRD), Functional Requirement Specifications (FRS), and Technical Design Documents (TDD).

- Prepare : 1. Test Strategy 2. Test Plan 3. Test Scenarios 4. Test Cases 5. Test Data 6. RTM (Requirement Traceability Matrix).

- Estimate testing effort.

- Participate in Sprint Planning and Grooming sessions.

9. Automation (Preferred) :

- Develop SQL-based automation scripts.

- Experience with ETL automation tools.

- Exposure to API Testing.

- Experience with CI/CD validation.

- Basic scripting knowledge in Python or Shell is preferred.

Required Technical Skills :

1. ETL Tools :

- Informatica PowerCenter, Informatica Cloud (IICS), Talend, SSIS, DataStage, ODI, Ab Initio (Preferred), AWS Glue (Preferred).

2. Databases :

- Oracle, SQL Server, PostgreSQL, MySQL, DB2, Snowflake, Teradata, Redshift.

3. SQL :

- Advanced SQL, PL/SQL, T-SQL, Stored Procedures, Functions, Packages, Triggers, Views, Cursors.

4. Data Warehouse :

- ETL Testing, Data Warehouse Testing, SCD Validation, Fact & Dimension Testing, Data Reconciliation, Data Profiling.

5. Testing Tools :

- JIRA, Azure DevOps, HP ALM, Quality Center, TestRail.

6. Version Control :

- Git, Bitbucket, SVN.

7. Scheduling Tools :

- Control-M, Autosys, Cron Jobs.

8. Cloud (Preferred) :

- AWS, Azure, Google Cloud Platform.

Required Qualifications :

- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

- 8+ years of experience in ETL Testing, Database Testing, and Data Warehouse QA.

- Strong expertise in Oracle and SQL Server databases.

- Excellent SQL and PL/SQL programming skills.

- Strong understanding of ETL architecture and data warehousing concepts.

- Experience validating large-scale enterprise databases.

- Experience with Agile/Scrum methodologies.

- Strong analytical and problem-solving skills.

- Excellent communication and stakeholder management abilities.

Preferred Skills :

- Banking or Financial Services domain experience.

- Insurance or Healthcare domain knowledge.

- Experience with Big Data testing.

- Knowledge of Hadoop ecosystem.

- Experience with Kafka data validation.

- Exposure to API and Microservices testing.

- Cloud data platform experience.

- Knowledge of DevOps and CI/CD pipelines.

- Familiarity with Data Governance and Data Quality frameworks.

Soft Skills :

- Strong analytical thinking, excellent troubleshooting skills, attention to detail, effective communication, team collaboration, time management, stakeholder management, mentoring junior QA engineers, and ability to work independently in a fast-paced environment.

Good to Have :

- Python scripting, Unix/Linux commands, Shell scripting, Power BI/Tableau data validation, knowledge of Data Lake architecture, exposure to AI/ML data testing, experience with REST API testing, and test automation using SQL/Python.

Roles & Responsibilities :

- Lead ETL and Database QA activities for enterprise data projects.

- Design comprehensive test strategies and execution plans.

- Validate complex ETL workflows and database transformations.

- Ensure data accuracy, completeness, consistency, and integrity.

- Collaborate with cross-functional teams to resolve data issues.

- Support production releases and post-deployment validation.

- Mentor junior QA engineers and enforce QA best practices.

- Drive continuous improvement in testing processes and quality standards.