Data Modeler

About Cognizant

Cognizant, a prominent global provider of information technology, consulting, and business process services based in Teaneck, New Jersey, is dedicated to assisting top companies worldwide in strengthening their operations. The company, listed on NASDAQ and a member of the Fortune 500 and Forbes Global 2000, is recognized among the fastest-growing and highest-performing firms globally.

Culture: Cognizant values passion, integrity, and experience as critical to its ongoing success. Employees thrive in a diverse, inclusive, and collaborative environment where their contributions to client service excellence are highly prized. The company actively promotes gender diversity and fosters equality, ensuring advancement is based solely on merit and achievement.

Role Summary

The Data Modeler is responsible for designing and developing scalable data models on modern data platforms. This role requires collaboration with business stakeholders, data architects, and engineering teams to establish solid data foundations, analytical marts, and business-ready data products. The ideal candidate will possess substantial expertise in data warehousing, dimensional modeling, data governance practices, and cloud analytics environments.

Key Responsibilities

• Design and upkeep of logical and physical data models.
• Specification of fact, dimension, and aggregate tables to support reporting and analytics.
• Development of scalable data structures facilitating business intelligence and data-driven decisions.
• Preparation and maintenance of source-to-target mappings and documentation.
• Definition of business rules, data relationships, and transformation logic.
• Creation of data models across raw, curated, and business/semantic layers.
• Application of Kimball dimensional modeling techniques to build and optimize models.
• Ensuring analytical data sets are consistent, reusable, and performant.
• Participating in enterprise data mart and data product development.
• Establishing data standards, naming conventions, and best modeling practices.
• Maintaining data lineage, metadata, and data dictionaries.
• Working with data governance teams to ensure compliance with data policies.
• Supporting data quality assurance and reconciliation processes.
• Collaborating with business analysts and stakeholders to gather reporting requirements.
• Facilitating design workshops and reviews.
• Translating business needs into scalable data solutions.
• Guiding data engineers through the implementation phase.

Essential Skills and Experience

• Proficiency in logical and physical data modeling and dimensional modeling using the Kimball methodology.
• Expertise in designing star and snowflake schemas, including fact and dimension tables.
• Familiarity with cloud data platforms such as Snowflake, Databricks, Azure, or AWS.
• Understanding of data pipelines, ETL/ELT processes, and data integration concepts.
• Experience with metadata management, data lineage tracking, data dictionaries, and frameworks for maintaining data quality.