IDMC Data Integration Engineer - Cloud-First ETL & Pipelines
Summary
Designs, builds, and operates enterprise ETL/data pipelines primarily on Informatica IDMC (IICS), including PowerCenter-to-IDMC migrations, Secure Agent operations, and CLAIRE-assisted development, across Azure, AWS, and GCP. Heavy AWS focus (Glue, S3, Step Functions, Athena) plus Terraform, Jenkins, and advanced SQL across Oracle, SQL Server, PostgreSQL, Redshift, and Databricks.
Data Integration Engineer specialized in designing, developing, and operating enterprise data pipelines using ETL tools, with Informatica IDMC (Intelligent Data Management Cloud / IICS) as the primary platform.
Able to work across cloud-agnostic environments, including Azure, AWS, and GCP.
REQUIRED TECHNICAL SKILLS
- Mapping Designer
- SQL ELT with pushdown optimization (full/source/target)
- Taskflows
- Dynamic Mappings
- Parameterization
- File listeners
- Performance tuning
Experience with batch and near-real-time ingestion from heterogeneous sources across:
- Mass Ingestion Databases (CDC)
- Files
- Applications
- Streaming
- Process Designer
- Service connectors
- Guides
- Business processes
- API and microservices integration
PowerCenter to IDMC
- Migration and modernization of on-premises pipelines
- Structured migration methodology
- CDI-PC
Platform Operations
- Administration of Secure Agents
- Secure Agent Groups
- Monitoring
- SLA management
AI-Assisted Development – CLAIRE
- CLAIRE GPT / CLAIRE Copilot: Assisted generation of mappings, debugging of transformations, and automated pipeline documentation through natural language within IDMC.
- Awareness of new agentic capabilities (CLAIRE Agents, Fall 2025 release) for headless ingestion and transformation flows.
Platform FinOps
- Understanding of the IPU (Informatica Processing Units) consumption model.
Cloud-Agnostic Technologies
AWS — Core to the Role
- AWS Glue
- Amazon S3
- AWS Step Functions
- Amazon Athena
Infrastructure as Code & CI/CD
- Terraform
- CloudFormation
- Jenkins
Databases & Platforms
- Advanced SQL: Oracle, SQL Server, PostgreSQL, Amazon Redshift, Databricks SQL
- Data Warehouse architecture patterns
- Data Lake architecture patterns
- Lakehouse architecture patterns
CERTIFICATIONS
Core
Relevant
Complementary
KEY RESPONSIBILITIES
- Design and implement ingestion, transformation, and distribution pipelines using CDI and Cloud Mass Ingestion.
- Develop data pipelines using the following AWS cloud services:
- AWS Glue
- Amazon S3
- AWS Step Functions
- Amazon Athena
- Extract and process data from heterogeneous sources using AWS services.
- Provide support for incidents related to data pipelines and data publishing, ensuring the quality and reliability of services provided to data users.
- EC2 Linux and Windows machines
- S3 buckets
- SNS
- EventBridge
- Operate and maintain integration infrastructure, including Secure Agents and runtime environments, across Azure and AWS while meeting SLA standards.
- Apply CLAIRE GPT / CLAIRE Copilot to optimize the mapping development lifecycle and improve development efficiency.