Informatica Cloud Developer

• Design, develop, and maintain data integration solutions using Informatica Intelligent Data Management Cloud (IDMC).

• Build and optimize data pipelines and workflows to support enterprise data processing and integration requirements.

• Develop and maintain robust ETL/ELT processes ensuring data quality, reliability, and scalability.

• Work closely with data engineers, architects, and business stakeholders to deliver efficient data integration solutions.

• Implement and manage cloud-based data integration workflows aligned with modern data platform practices.

• Write and optimize advanced SQL and PL/SQL queries for efficient data processing and transformation.

• Ensure best practices in data integration design, performance tuning, and error handling.

• Support data platform initiatives by integrating cloud services and enterprise data systems.

• Contribute to automation and scripting tasks using Unix Shell scripting or Python when required.

• Participate in troubleshooting, performance optimization, and continuous improvement of data integration environments.

• Strong hands-on experience with Informatica Intelligent Data Management Cloud (IDMC).

• Certification in Informatica Cloud / IDMC.

• Advanced knowledge of SQL and PL/SQL for complex data transformations and integrations.

• Experience working with cloud-based environments, particularly within the Azure ecosystem.

• Understanding of data engineering principles and cloud data integration architectures.

• Familiarity with data pipeline development, ETL/ELT processes, and data transformation frameworks.

• Exposure to Azure data services or cloud infrastructure concepts.

• Experience working in enterprise data integration environments.

You Should Possess the Ability to:

• Design scalable and efficient cloud-based data integration solutions.

• Analyze complex data integration requirements and translate them into robust technical implementations.

• Optimize data workflows and queries for performance and reliability.

• Collaborate with cross-functional teams across data engineering, architecture, and analytics.

• Troubleshoot and resolve data integration and performance issues effectively.

• Contribute to continuous improvement of data platform architecture and integration practices.