Data Modeler

NTT DATA's Client is 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.

Develop and maintain:

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

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

• 12+ 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 data models.

Deep understanding of:
Relational data modeling
Dimensional modeling
Star and snowflake schemas
Normalization and denormalization
Entity-relationship modeling
Data warehousing concepts

• Strong understanding of facts, dimensions, hierarchies, grain, surrogate keys, business keys, and Slowly Changing Dimensions.
• Strong experience defining entities, attributes, relationships, cardinality, primary/foreign keys, and referential-integrity rules.
• Experience translating complex business requirements into enterprise data structures and models.
• 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.

For more than 25 years, NTT DATA Services have focused on impacting the core of your business operations with industry-leading outsourcing services and automation. With our industry-specific platforms, we deliver continuous value addition, and innovation that will improve your business outcomes. Outsourcing is not just a method of gaining a one-time cost advantage, but an effective strategy for gaining and maintaining competitive advantages when executed as part of an overall sourcing strategy.


About NTT DATA Services:

NTT DATA Services is a recognized leader in IT and business services, including cloud, data and applications, headquartered in Texas. As part of NTT DATA, a $30 billion trusted global innovator with a combined global reach of over 80 countries, we help clients transform through business and technology consulting, industry and digital solutions, applications development and management, managed edge-to-cloud infrastructure services, BPO, systems integration and global data centers. We are committed to our clients' long-term success. Visit nttdata.com or LinkedIn to learn more.

NTT DATA Services is an equal opportunity employer and considers all applicants without regarding to race, color, religion, citizenship, national origin, ancestry, age, sex, sexual orientation, gender identity, genetic information, physical or mental disability, veteran or marital status, or any other characteristic protected by law. We are committed to creating a diverse and inclusive environment for all employees. If you need assistance or an accommodation due to a disability, please inform your recruiter so that we may connect you with the appropriate team.

Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting hourly range for this remote role is ($x - x/hourly ). This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on several factors, including the candidate's actual work location, relevant experience, technical skills, and other qualifications.

This position is eligible for company benefits that will depend on the nature of the role offered. Company benefits may include medical, dental, and vision insurance, flexible spending or health savings account, life, and AD&D insurance, short-and long-term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally required benefits.