NTT DATA seeks a skilled Data Modeler to join our Enterprise Data Architecture & Modeling team. This role focuses on designing, developing, and maintaining scalable enterprise data models to support various initiatives including analytics, reporting, operational applications, data warehousing, and data integration.

You will collaborate with stakeholders across business, data architecture, engineering, and governance teams. The goal is to translate intricate business needs into robust conceptual, logical, and physical data models.

Ideal candidates possess extensive experience in enterprise data modeling, relational and dimensional modeling techniques, data warehousing, cloud data platforms, metadata management, and data governance. Establishing consistent data definitions, standards, and modeling practices across diverse business domains and technologies is key.

Key responsibilities include designing and maintaining conceptual, logical, and physical data models for enterprise platforms and applications. You will translate business requirements into scalable data structures, developing relational and dimensional models, star schemas, snowflake schemas, and domain-oriented models. Defining entities, attributes, relationships, and keys is crucial.

Responsibilities extend to designing dimensional models for data warehouses and marts, defining facts, dimensions, and measures. You will also manage historical information using techniques like Slowly Changing Dimensions (SCDs) and ensure models support reporting and advanced analytics needs. Collaborating with Data Engineers to integrate models into ETL/ELT pipelines is essential.

Furthermore, you will define and enforce data modeling standards, naming conventions, and best practices. Establishing consistent definitions for critical business data and supporting master data management, metadata, and data governance initiatives are core duties. You will also maintain comprehensive documentation for models, including business definitions, lineage, and transformation rules, while contributing to data quality frameworks by identifying mandatory/optional elements, relationships, and constraints.

Candidates must have over 10 years of experience in data management, architecture, or warehousing, with at least 7 years focused on developing conceptual, logical, and physical data models. A deep understanding of relational and dimensional modeling, normalization/denormalization, entity-relationship modeling, and data warehousing concepts is required.

Essential skills include a strong grasp of facts, dimensions, hierarchies, grain, keys, and Slowly Changing Dimensions. You should be adept at defining entities, attributes, relationships, cardinality, keys, and referential-integrity rules. Experience translating complex business requirements into enterprise data structures is a must, alongside strong knowledge of SQL and relational database concepts.

Experience with modern cloud data platforms, data lakes, data warehouses, or lakehouse architectures is necessary. Familiarity with ETL/ELT processes, data integration patterns, metadata management, data lineage, and data governance is also expected. Experience working with enterprise architecture, Data Engineering, analytics, and application development teams is beneficial. Proficiency with enterprise data modeling tools like ER/Studio, ERwin, or similar is required.