Must be strong in Informatica Cloud Architecture and design knowledge
Hands-on knowledge about setting up Informatica cloud? Must be strong in Informatica Cloud features like Agent configuration, task automation, deployments of task flows across different environment etc.
Design and develop data integration workflows and mappings using IICS/IDMC
Good understanding across Cloud and infrastructure components (server, data, and applications)
Collaborate with data architects and analysts to understand data requirements and objectives? Maintain and support existing data integration solutions.
Optimize and enhance performance of data workflows and mappings.? Implement and manage data quality and data governance policies.
Troubleshoot and resolve data integration issues.
Ensure data accuracy, integrity, and security in all data integration activities
Experience in building data integration processes by constructing mappings, tasks, task flows, schedules, and parameter files
Experience in developing application integration using SOAP/REST APIs, APIs leveraged to integrate multiple systems
Good knowledge on JMS Queues processing, configuring and monitoring them
Understand pain points from a customer/vertical perspective for developing specific solutions. Identify the customer segment to position the new offering and develop business case for the new service offering
Analyzing data integration requirements, analyzing data sources and targets, business rules, and transformation logic
Analyzes the impact of changes on existing ETL/ELT processes and systems. Assesses the compatibility with goals in all areas. Analyzes cost effectiveness and feasibility
Create functional design for overall business intelligence solutions
Design, develop and maintain Informatica cloud data integration processes using the appropriate data load technique, including Push-Down Optimization for performance optimization
Design data integration and conversion strategy, exception handing mechanism, data retention and archival strategy
Designing and developing data extraction, cleansing, transformation, and loading processes and workflows to load data
Debug and tune data integration processes; analyze data warehouse architecture, normalized/de-normalized, star schemas and snowflakes, slowly changing dimensions, dimensional surrogate key handling, exception data processing, troubleshoot and recommend improvements and alternate methodologies