Skill- IDMC Developer

Experience- 4+ Years

Define IDMC architecture for Client ingestion, transformation, data quality, orchestration and metadata management.

Design reusable ingestion frameworks for Oracle, non-Oracle, file-based, API-based and database sources.

Establish IDMC standards for mappings, mapping tasks, taskflows, parameterization and deployment structure.

Assess existing Informatica PowerCenter repositories, mappings, workflows, sessions, and reusable components to determine migration readiness to IDMC.

Analyze migration impacts, identify unsupported objects, and recommend remediation or redesign strategies for IDMC compatibility.

Migrate and convert PowerCenter ETL processes, mappings, workflows, parameter files, and schedules to Informatica IDMC.

Develop and configure IDMC Mapping Tasks, Taskflows, Data Integration Pipelines, and Secure Agent environments.

Re-engineer legacy ETL logic using cloud-native Informatica IDMC capabilities, reusable frameworks, and best practices.

Configure and manage source and target connections from IDMC to Oracle databases, ADW, OCI Object Storage, flat files, APIs,

Perform source-to-target validation, reconciliation testing, and data quality checks to ensure successful migration.

Troubleshoot Informatica to IDMC migration issues related to transformations, connectivity, performance, and workflow execution

Establish integration architecture for batch, CDC and near real-time data movement using oldenGate and IDMC.

Define ADW warehouse design patterns for analytical workloads, semantic consumption and reporting performance.

Build ingestion pipelines from source systems into OCI Object Storage and ADW.

Develop transformation workflows for Bronze, Silver and Gold layer processing.

Implement incremental load, full load, CDC-based load and historical data migration patterns.

Build data quality checks, validation rules, audit columns and reconciliation routines.

Develop SQL, IDMC and data engineering components for scalable data processing.

Troubleshoot data pipeline failures, performance issues and data mismatches.

Support operational monitoring, deployment and production support of ETL jobs.

Prior hands-on experience in Data Lake, Data Warehouse, ETL modernization or Analytics transformation projects.