Key Responsibilities
Design and implement ingestion, transformation, and distribution pipelines with CDI and Cloud Mass Ingestion.
Build and optimize ingestion and ELT into the Databricks Lakehouse using IDMC for Databricks and Delta Lake patterns.
Migrate PowerCenter workloads to IDMC using structured methodology and internal accelerators.
Operate and maintain integration infrastructure (Secure Agents, runtimes) on Azure and AWS under SLA standards.
Apply CLAIRE GPT/Copilot to optimize the mapping development cycle and reduce delivery time.
Requirements
Technical Skills
Informatica IDMC · Integration Core
Cloud Data Integration (CDI): Mapping Designer, SQL ELT with pushdown optimization (full/source/target), Taskflows, mapping partitioning, Dynamic Mappings, parameterization, file listeners, intelligent structure models (CLAIRE-powered), and performance tuning.
Cloud Mass Ingestion (CMI): batch and near-real-time ingestion from heterogeneous sources across its variants: Mass Ingestion Databases (CDC), Files, Applications, and Streaming.
Cloud Application Integration (CAI): Process Designer, service connectors, guides, and business processes; API and microservices integration.
PowerCenter to IDMC: migration and modernization of on-premises pipelines using structured methodology, CDI-PC, and migration accelerators.
Platform operations: administration of Secure Agents and runtime environments (Secure Agent Groups), monitoring, and SLA management.
Databricks Integration
IDMC for Databricks: ingestion and ELT into the Databricks Lakehouse with CDI and Cloud Mass Ingestion, Delta Lake load patterns, and SQL ELT pushdown to Databricks SQL.
Connectivity through the Databricks connector (Partner Connect), Unity Catalog awareness, and parameterized job orchestration.
AI-Assisted Development (CLAIRE)
CLAIRE GPT / CLAIRE Copilot: assisted generation of mappings, debugging of transformations, and automatic pipeline documentation through natural language within IDMC.
Awareness of the 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 and per-service cost optimization.
Cloud-Agnostic (Complementary)
Azure: Azure Data Factory (ADF), Data Lake Storage Gen2, Key Vault, Azure Databricks.
AWS: Glue, S3, Step Functions, Redshift, Athena, EventBridge.
GCP (desirable): BigQuery, Cloud Composer.
IaC & CI/CD for pipelines: Terraform, CloudFormation; GitHub/Bitbucket, Jenkins.
Databases & Platforms
Advanced SQL (Oracle, SQL Server, PostgreSQL, Redshift, Databricks SQL).
NoSQL (MongoDB, DynamoDB; desirable).
Data Warehouse, Data Lake, and Lakehouse architecture patterns.
Certifications
Informatica Cloud Data Integration Developer, Professional Certification (ICP) (core to the role).
Informatica Cloud Application Integration Developer, Professional Certification (desirable).
Informatica IDMC Foundation / Data Engineering Foundation.
Databricks Certified Data Engineer Associate (desirable).
Microsoft Certified: Azure Data Engineer Associate (DP-203) (complementary).
AWS Certified Data Engineer / Data Analytics Specialty (complementary).
Why NTT Data?
Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.
NTT Data is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. NTT Data is an Equal Opportunity Employer Male/Female/Disabled/Veteran and a VEVRAA Federal Contractor.
