Data Modeller

Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.

Our Culture:

Your passion, integrity and experience are integral to Cognizant's success. You will join a dynamic and expanding global leader in IT and Business consultancy where you will be valued for who you are. We take pride in our partnership with our clients, so your ability to add value and provide exceptional service to our clients is fundamental to your success. In return, you will be presented with opportunities to develop your career and collaborate with talented colleagues in a supportive, diverse environment.

At Cognizant we recognize that companies that are open and welcoming to a multi-culturally diverse workforce will thrive with fresh perspectives and collaborative knowledge. Cognizant focuses on promoting & increasing gender diversity and providing a workplace which encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.

Job Summary:

We are seeking an experienced Data Modeler with strong hands-on expertise in Erwin Data Modeler, Azure data technologies, PySpark, and SQL. The candidate will translate complex business requirements into scalable conceptual, logical, and physical data models for enterprise data platforms, data warehouses, lakehouses, analytics, and reporting solutions. The role requires close collaboration with business stakeholders, data architects, data engineers, analysts, governance teams, and downstream consumers to deliver standardized, reusable, secure, and high-performing data structures.

Responsibilities:

• Design, develop, and maintain conceptual, logical, and physical data models for operational, analytical, data warehouse, and lakehouse solutions.
• Use Erwin Data Modeler to create entity-relationship models, dimensional models, domain models, naming standards, subject-area models, and physical database designs.
• Translate business requirements, data discovery findings, and source-system structures into clear entities, attributes, relationships, keys, hierarchies, and business rules.
• Design normalized, denormalized, dimensional, Data Vault, and domain-oriented models based on solution requirements and consumption patterns.
• Create fact and dimension models, define grain, measures, surrogate keys, conformed dimensions, hierarchies, and slowly changing dimension strategies.
• Develop and maintain source-to-target mappings, data dictionaries, metadata definitions, transformation rules, business glossaries, and model documentation.
• Perform data discovery, profiling, reverse engineering, and impact analysis using SQL and PySpark across large structured and semi-structured datasets.
• Partner with data engineers to implement models on Azure Synapse Analytics, Azure Databricks, Azure SQL Database, Azure Data Lake Storage Gen2, Delta Lake, and related Azure services.
• Define schema designs, partitioning approaches, file layouts, data types, indexing considerations, and storage patterns that support performance, scalability, and cost efficiency.
• Validate model implementation through complex SQL queries, PySpark notebooks, reconciliation checks, and data-quality controls.
• Review transformation logic and ETL/ELT pipelines to confirm alignment with approved data models and source-to-target specifications.
• Manage model changes, version control, schema evolution, dependencies, and impact assessments across upstream and downstream systems.
• Contribute to metadata management, data lineage, data classification, governance, privacy, retention, and security requirements.
• Facilitate modelling workshops and design reviews with architects, business analysts, product owners, engineering teams, and business subject-matter experts.
• Support testing, defect analysis, production issue resolution, performance tuning, audit requirements, and continuous model improvement.
• Establish and promote enterprise data-modelling standards, reusable patterns, naming conventions, and documentation practices.

Required Skills:

• 8–15 years of overall IT experience, including at least 5 years in data modelling, data architecture, analytics engineering, or enterprise data-management roles.
• Minimum 3 years of hands-on experience with Erwin Data Modeler in complex enterprise environments.
• Proven delivery experience on Azure-based data warehouse, lakehouse, analytics, migration, or modernisation programmes.
• Strong evidence of designing models for large datasets and supporting their implementation through SQL, PySpark, and Azure technologies.

Benefits:

Joining Cognizant will give you the opportunity to learn and collaborate with some of the most talented people in the industry, while having your finger on the pulse of emerging industry trends and working on the cutting edge of technology in your field of expertise.

We recognize that our people perform at their best when they feel valued as significant contributors and that is why at Cognizant, taking care of our employees is a priority:

· You can pursue innovative career tracks and opportunities here

· You can enhance your professional development through education and dedicated training

· We’ll give you the skills you need to keep pace with the changing workplace while our compensation, benefits and wellness packages help you stay healthy and plan for the future.

Next Steps:

Please reach out to our friendly and welcoming team today to apply and register your interest in this full-time role. We'd love to help you get your next role and enable you to fulfil your professional ambitions.