Data Modeler

NTT DATA BUSINESS SOLUTIONS; Dadri, Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Noida/Gurgaon, India, seeks an AI Data Modeller Consultant to translate business and AI requirements into scalable data models. You will design enterprise data models, optimize SQL, and work with vector stores and data governance across structured and unstructured data.

Candidate should have strong experience in data architecture, metadata management, and regulatory considerations, with a focus on AI/ML data needs and RAG pipelines.

Qualifications

• Strong enterprise data modeling and database design.
• Advanced SQL with schema design, joins, indexing, and query optimization.
• Designing models for relational databases, data warehouses, data lakes, and analytics platforms.
• Understanding AI/ML data requirements including embeddings, vector stores, semantic search, metadata filtering, feature engineering, and RAG pipelines.
• Working with structured, semi-structured, and unstructured data.

Skills

Enterprise data modeling

Advanced SQL

Data architecture

Metadata management

Data governance

Privacy & access control

AI/ML data requirements

Vector stores

Knowledge graph

Tools

OpenSearch

FAISS

Pinecone

pgvector

AWS

Azure

Google Cloud

Job description

Job Summary

AI Data Modeller Consultant

We are currently seeking a Data Modeler to join our team in Noida / Gurgaon, Delhi (IN-DL), India (IN).

Required Skills

• Strong experience in enterprise data modeling, database design, metadata management, and data architecture.
• Advanced SQL skills, including schema design, joins, indexing, query optimization, stored procedures, data validation, and analytical querying.
• Experience designing models for relational databases, data warehouses, data lakes, analytics platforms, and enterprise applications.
• Understanding of AI/ML data requirements, including embeddings, vector stores, semantic search, metadata filtering, feature engineering, and RAG pipelines.
• Experience working with structured, semi-structured, and unstructured data.
• Knowledge of data quality, data lineage, data governance, privacy, access control, and regulatory considerations.
• Ability to translate business and AI requirements into practical, scalable data models.

Preferred Skills

• Experience in financial services, market intelligence, ratings, commodities, risk, capital markets, or regulated data environments.
• Experience with vector databases such as OpenSearch, FAISS, Pinecone, or pgvector.
• Experience with graph databases, ontologies, semantic models, or knowledge graph technologies.
• Familiarity with cloud data platforms on AWS, Azure, or Google Cloud.
• Experience with data cataloging, metadata management, lineage tools, and enterprise governance platforms.
• Experience supporting LLM applications, AI agents, RAG systems, intelligent search, or intelligent document processing.