Data Modeling engineers

Vg Consultancy Greater Noida; Hyderabad, Gurugram District, Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Vg Consultancy Greater Noida is seeking an experienced Data Modeling Engineer to design, develop, and maintain scalable enterprise data models supporting analytics, AI, and ML initiatives.

The role emphasizes conceptual, logical, and physical modeling, metadata management, data governance, and AI-ready architectures, collaborating with data engineers, AI engineers, and stakeholders.

Qualifications

• Bachelor's or Master's degree in CS, IS, data engineering or related field.
• Strong experience in data modeling using conceptual, logical, and physical approaches.
• Expertise in SQL and relational database design.
• Experience with enterprise databases (SQL Server, Oracle, PostgreSQL, MySQL, Snowflake).
• Hands-on data warehousing, dimensional modeling (Star/Snowflake), and data lakes.
• Experience with metadata management, data lineage, data quality, and governance.
• Understanding of AI-ready data design, embeddings, semantic search, and RAG.

Responsibilities

• Design and maintain conceptual, logical, and physical data models for enterprise apps.
• Develop scalable database schemas, relationships, indexes, and optimized SQL.
• Create AI-ready data models to support LLMs and RAG pipelines.
• Design metadata structures for documents, embeddings, and vector stores.
• Develop data dictionaries and metadata documentation.
• Implement data quality rules, validation, and reconciliation processes.
• Define data lineage, governance, and master data management standards.
• Collaborate with Data Engineers on ETL/ELT, data lakes, and warehouses.
• Model relational and dimensional structures for reporting/analytics.
• Support structuring data for RAG and Knowledge Graphs with AI Engineers.
• Ensure compliance with enterprise data architecture, governance, and security.
• Create ER diagrams, technical docs, and knowledge transfer materials.

Skills

Data Modeling

Conceptual Modeling

Logical Modeling

Physical Modeling

SQL

Relational Databases

Data Warehousing

Data Lakes

Enterprise Data Architecture

Metadata Management

Data Governance

AI-ready Data

RAG Design

Semantic Search

Knowledge Graphs

Vector Databases

Snowflake

SQL Server

Oracle

PostgreSQL

MySQL

Cloud (AWS, Azure, GCP)

Education

Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field

Tools

Erwin

ER/Studio

Visio

Lucidchart

Job description

Role Overview

We are looking for an experienced Data Modeling Engineer to design, develop, and maintain scalable enterprise data models that support analytics, reporting, AI, and machine learning initiatives. The ideal candidate will have strong expertise in conceptual, logical, and physical data modeling, SQL, metadata management, data governance, and AI-ready data architecture. This role will collaborate closely with Data Engineers, AI Engineers, Architects, and Business stakeholders to build high-quality, governed data assets for enterprise applications and AI-powered solutions.

Key Responsibilities

• Design and maintain conceptual, logical, and physical data models for enterprise applications and data platforms.
• Develop scalable database schemas, relationships, indexes, and optimized SQL queries.
• Create AI-ready data models to support LLMs, RAG pipelines, semantic search, and AI applications.
• Design metadata structures for document processing, embeddings, and vector databases.
• Develop data dictionaries, business glossaries, and metadata documentation.
• Implement data quality rules, validation logic, and reconciliation processes.
• Define and maintain data lineage, governance, and master data management standards.
• Collaborate with Data Engineers to support ETL/ELT pipelines, data lakes, and data warehouses.
• Design and optimize relational and dimensional data models for reporting and analytics.
• Work with AI Engineers to structure data for Retrieval-Augmented Generation (RAG) and Knowledge Graph implementations.
• Ensure compliance with enterprise data architecture, governance, and security standards.
• Create ER diagrams, technical documentation, and knowledge transfer materials.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Strong experience in data modeling using conceptual, logical, and physical modeling techniques.
• Expertise in SQL and relational database design.
• Experience with enterprise databases such as SQL Server, Oracle, PostgreSQL, MySQL, or Snowflake.
• Hands-on experience with data warehousing, dimensional modeling (Star/Snowflake schema), and data lakes.
• Experience with metadata management, data lineage, data quality, and data governance.
• Understanding of AI-ready data design, embeddings, semantic search, and RAG architectures.
• Knowledge of vector databases such as Pinecone, FAISS, Weaviate, Milvus, OpenSearch, or pgvector.
• Experience with ER modeling tools such as Erwin, ER/Studio, Visio, or Lucidchart.
• Strong analytical, problem-solving, and documentation skills.

Preferred Qualifications

• Experience in financial services, banking, healthcare, or other regulated industries.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Experience with Knowledge Graphs, ontologies, and semantic data modeling.
• Knowledge of modern data catalog and governance tools such as Microsoft Purview, Collibra, Alation, or Informatica.
• Experience supporting AI/ML initiatives with structured and unstructured enterprise data.

Key Skills

• Data Modeling
• Conceptual, Logical & Physical Data Models
• SQL
• Relational Databases
• Data Warehousing
• Data Lakes
• Enterprise Data Architecture
• Metadata Management
• Data Governance
• Data Quality-?caret? Actually forgot to close li
• Data Lineage
• ER Modeling
• AI-Ready Data
• RAG Data Design
• Semantic Search
• Knowledge Graphs
• Vector Databases (Pinecone, FAISS, Weaviate, Milvus, pgvector, OpenSearch)
• Snowflake, SQL Server, Oracle, PostgreSQL, MySQL
• Cloud (AWS, Azure, GCP)