ETL Informatica Test Engineer - Investment Management & Financial Services Domain

Note : We have to look at profiles from financial domain, we can also look at profiles who dont have Informatica but have experience working on complex SQL queries

Key Responsibilities :

- Design, develop, and execute comprehensive test strategies and plans focused on data integrity, consistency, and completeness across the Data Platform.

- Validate data ingestion, transformation, mapping, and enrichment processes from multiple sources (e.g., market data, reference data, positions, transactions).

- Develop and execute automated and manual data validation scripts and test cases across data layers (staging, integration, reporting).

- Collaborate closely with Data Architects, Business Analysts, and Engineers to define quality benchmarks and resolve data anomalies.

- Perform RCA of data quality issues, coordinate with development and data operations teams to ensure timely resolution.

- Document test results and create detailed defect reports and QA documentation.

- Contribute to the improvement of the data quality framework and test automation practices across the Data ecosystem.

- Support data reconciliation efforts across front, middle, and back-office platforms, ensuring alignment with portfolio management, trading, and accounting systems.

- Participate in agile ceremonies (sprint planning, daily stand-ups, retrospectives) and contribute to release readiness.

Required Skills & Qualifications :

- 4+ years of experience in a QA/Data Quality role, preferably within the investment management or financial services industry.

- Strong knowledge of front-to-back office data flows and investment data domains (securities, pricing, positions, transactions, benchmarks, analytics).

- Experience working with the Alpha Data Platform (ADP) or similar platforms (e.g., State Street Alpha, BlackRock Aladdin, SimCorp, Charles River).

- Hands-on experience in writing and executing SQL queries for data validation and testing.

- Familiarity with data quality tools and test automation frameworks (e.g., Informatica DQ, Tricentis, Selenium, Python, or similar).

- Strong understanding of data governance, data lineage, and master/reference data management principles.

- Proven ability to identify, troubleshoot, and resolve complex data-related issues.

- Excellent communication skills and the ability to collaborate effectively with cross-functional teams