Enterprise Data Modeler

NTT DATA Global Delivery Services Ltd; Bengaluru; Presencial; INR 800.000 - 1.600.000; Jornada completa

Descripción de la vacante

NTT DATA is seeking a Senior Data Modeler to design, develop, and maintain enterprise data models supporting analytics, reporting, and data integration. The role requires 10+ years in data modeling, strong SQL skills, and hands-on experience with relational and dimensional modeling.

You will work across data warehousing, metadata management, and governance initiatives, collaborating with data engineers and architects.

Formación

• 10+ years of experience in data management, data architecture, data warehousing, or related disciplines, with significant hands-on data-modeling experience.
• 7+ years of strong experience developing conceptual, logical, and physical models.
• Strong knowledge of SQL and relational database concepts.
• Experience with cloud data platforms, data lakes, data warehouses, or lakehouse architectures.
• Knowledge of metadata management, data lineage, governance, and data dictionaries.
• Experience working with enterprise architecture, data engineering, analytics, and application-development teams.
• Familiarity with Agile delivery methodologies and enterprise architecture frameworks.

Responsabilidades

• Design, develop, and maintain conceptual, logical, and physical data models for enterprise data platforms and analytics solutions.
• Translate complex business requirements into scalable data structures.
• Collaborate with Data Engineers to implement models within ETL/ELT pipelines.
• Define entities, attributes, relationships, keys, and hierarchies across domains.
• Maintain documentation on business definitions, data lineage, and governance rules.
• Ensure models support reporting, BI, and regulatory/compliance needs.

Conocimientos

Relational modeling

Dimensional modeling

Star schemas

Snowflake schemas

ER modeling

Data warehousing

SCDs

MDM & governance

Metadata management

SQL proficiency

Herramientas

ER/Studio

ERwin Data Modeler

SAP PowerDesigner

Visio

Lucidchart

Descripción del empleo

Data Modeler Req ID: 395801 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, forward-thinking organization, we are currently seeking a Data Modeler to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

Job Description – Data Modeler

Role Title: Data Modeler – Enterprise Data Architecture & Modeling

Location: PAN India

Experience: 10+ years of overall experience, with strong hands‑on experience in enterprise data modeling.

Position Summary We are seeking an experienced Data Modeler to design, develop, and maintain scalable enterprise data models supporting analytics, reporting, operational applications, data warehousing, and data integration initiatives. The Data Modeler will collaborate closely with business stakeholders, Data Architects, Data Engineers, analysts, application teams, and governance teams to translate complex business requirements into well‑defined conceptual, logical, and physical data models. The ideal candidate will have strong hands‑on experience in enterprise data modeling, relational and dimensional modeling, data warehousing, cloud data platforms, metadata management, and data governance. The role requires the ability to establish consistent data definitions, relationships, standards, and modeling practices across multiple business domains and technology platforms.

Key Responsibilities

Enterprise Data Modeling

Design, develop, and maintain conceptual, logical, and physical data models for enterprise data platforms, analytics solutions, and business applications.

Translate complex business requirements, business processes, and data requirements into scalable and reusable data structures.

• Relational data models
• Dimensional data models
• Star schemas
• Snowflake schemas
• Domain‑oriented data models

Define entities, attributes, relationships, primary keys, foreign keys, business keys, hierarchies, and reference‑data structures.

Design models that appropriately support transactional, analytical, historical, and reporting requirements.

Perform model normalization and denormalization based on application, integration, analytics, and performance requirements.

Data Warehousing & Analytics Modeling

Design dimensional models for enterprise data warehouses, data marts, and modern analytics platforms.

Define facts, dimensions, measures, hierarchies, and grain based on business and analytical requirements.

Design appropriate approaches for maintaining historical information, including Slowly Changing Dimensions (SCDs). Ensure models support reporting, BI, advanced analytics, and downstream data‑consumption requirements.

Partner with Data Engineers to ensure models can be effectively implemented within ETL/ELT and data‑processing pipelines.

Data Standards & Governance

Define and enforce enterprise data‑modeling standards, naming conventions, data types, and modeling best practices.

Partner with business and technical stakeholders to establish consistent definitions for critical business data.

Support master data, reference data, metadata management, and data‑governance initiatives. Identify authoritative data sources and help establish consistent definitions and relationships across enterprise systems.

Contribute to the development and maintenance of business glossaries and data dictionaries. Participate in architecture and model design reviews to ensure proposed solutions comply with enterprise architecture and governance standards.

Metadata, Lineage & Documentation

Maintain comprehensive documentation for conceptual, logical, and physical data models.

Document: Business definitions, Data entities and attributes, Source‑to‑target relationships, Data lineage, Business rules, Data ownership, Transformation requirements.

Maintain model metadata using enterprise modeling and/or data‑cataloging platforms. Ensure appropriate traceability between business requirements, source systems, data models, transformation logic, and downstream consumption.

Data Quality & Integrity

Contribute to data‑quality frameworks by identifying: Mandatory and optional data elements, Valid relationships, Referential‑integrity requirements, Data constraints, Validation rules, Business rules.

Work with Data Engineering and Data Governance teams to identify and resolve data‑quality and consistency issues. Ensure models appropriately support auditability, historical tracking, lineage, and data traceability. Identify data redundancies, inconsistencies, and opportunities for standardization and reuse.

Required Skills & Experience

10+ years of experience in data management, data architecture, data warehousing, or related disciplines, with significant hands‑on data‑modeling experience. 7+ years of strong experience developing conceptual, logical, and physical models.

• Relational data modeling
• Dimensional modeling
• Star and snowflake schemas
• Normalization and denormalization
• Entity‑relationship modeling
• Data warehousing concepts
• Facts, dimensions, hierarchies, grain, surrogate keys, business keys, and Slowly Changing Dimensions
• Defining entities, attributes, relationships, cardinality, primary/foreign keys, and referential‑integrity rules

• Strong knowledge of SQL and relational database concepts.
• Experience with modern cloud data platforms, data lakes, data warehouses, or lakehouse architectures.
• Understanding of ETL/ELT processes and data‑integration patterns.
• Experience with metadata management, data lineage, data dictionaries, and business glossaries.
• Good understanding of Master Data Management (MDM), reference data, data quality, and data governance.
• Experience working with enterprise architecture, Data Engineering, analytics, and application‑development teams.

Data Modeling Tools

Hands‑on experience with one or more enterprise data‑modeling tools such as:

• ER/Studio
• ERwin Data Modeler
• SAP PowerDesigner
• Visio
• Lucidchart
• Or equivalent enterprise modeling platforms

Cloud & Technology Experience

Experience with one or more modern data platforms is preferred, including:

• Snowflake
• Databricks
• Microsoft Azure / Azure Synapse
• AWS data services
• Google Cloud Platform / BigQuery
• SQL Server
• Oracle
• PostgreSQL or other enterprise relational databases

Exposure to modern architectures such as data lakehouse, data mesh, domain‑oriented data architecture, and cloud‑native analytics platforms is an advantage.

Preferred Qualifications

• Experience supporting large‑scale enterprise data‑transformation or modernization programs.
• Experience modeling data across multiple business domains and source systems.
• Experience working in complex environments involving both operational and analytical data.
• Knowledge of data cataloging and governance platforms such as Collibra, Alation, Microsoft Purview, or equivalent tools.
• Understanding of data privacy, security, retention, and regulatory requirements.
• Experience working in Healthcare, Life Sciences, Pharmaceutical, or other regulated industries is preferred.
• Familiarity with Agile delivery methodologies and enterprise architecture frameworks.

Key Competencies

• Strong analytical and problem‑solving skills.
• Ability to understand complex business processes and translate them into structured data models.
• Strong attention to detail and commitment to data consistency and quality.
• Ability to communicate data concepts effectively to both technical and non‑technical stakeholders.
• Strong collaboration skills across business, architecture, engineering, governance, and analytics teams.
• Ability to independently lead data‑modeling discussions and design reviews.

Ideal Candidate Profile

The ideal candidate is a hands‑on enterprise Data Modeler, rather than primarily a Data Engineer or BI Developer, who can demonstrate substantial experience creating and governing conceptual, logical, and physical models. Candidates should be able to provide concrete examples of enterprise data models they have designed, explain their approach to relational versus dimensional modeling, and demonstrate strong knowledge of data warehousing, SCDs, metadata, lineage, governance, and modern cloud data architectures.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise‑scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start‑up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D. Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in‑office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

Equal Opportunity Employer

NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here . If you'd like more information on your EEO rights under the law, please click here . For Pay Transparency information, please click here . Experience Level Senior Level