IDQ Quality Engineer (4-8 yrs)

About the Job :

We are seeking a highly motivated and skilled Quality Engineer with a strong focus on Test Data Management to join our dynamic team.

In this role, you will be instrumental in ensuring the integrity, accuracy, and quality of test data utilized across our diverse systems.

Key Responsibilities :

Data Quality Assessment :

- Leverage Informatica Data Quality (IDQ) to conduct comprehensive data discovery and profiling.

- Identify and analyze data anomalies, inconsistencies, and quality issues.

Data Standardization & Cleansing :

- Design and implement robust data standardization processes to ensure consistent data formats, values, and structures.

Data Quality Rule Development :

- Develop, implement, and manage a comprehensive suite of data quality rules within the IDQ environment to enhance data accuracy and reliability.

Cross-functional Collaboration :

- Collaborate effectively with cross-functional teams (e.g, development, testing, data engineering) to identify and resolve data quality issues proactively.

Documentation & Reporting :

- Create and maintain detailed documentation for all data quality processes, rules, and standards.

- Generate regular reports on key data quality metrics to track progress and drive continuous improvement.

Continuous Improvement :

- Actively participate in initiatives to improve data quality processes and methodologies.

Qualifications :

Essential :

- Proven experience with Informatica Data Quality (IDQ), encompassing data discovery, profiling, rule creation, and data cleansing.

- Strong understanding of data quality best practices, methodologies, and standards.

- Experience in designing and implementing data standardization and cleansing processes.

- Excellent analytical and problem-solving skills with the ability to identify and resolve complex data quality issues.

- Strong collaboration and communication skills with the ability to effectively interact with diverse teams.

Desirable :

- Experience with Agile development methodologies.

- Knowledge of scripting languages (e.g, Python, SQL).

- Experience with data warehousing and data lake technologies.

- Relevant certifications (e.g, Informatica certifications)