Data Modeller

About Cognizant

Cognizant (NASDAQ: CTSH) is a global leader in information technology, consulting, and business process services headquartered in Teaneck, New Jersey. The company specializes in driving stronger business outcomes through innovative technology solutions combined with extensive industry expertise and a collaborative global workforce. Recognized among the NASDAQ-100, S&P 500, Forbes Global 2000, and Fortune 500, Cognizant ranks as one of the fastest growing and top-performing companies worldwide.

Our Culture

At Cognizant, your passion, integrity, and experience are highly valued. You will join a thriving international IT and business consultancy where your contributions and client service excellence are crucial to success. The company fosters career growth through opportunities to work alongside skilled professionals in a diverse, inclusive, and supportive environment that promotes gender diversity and equal opportunity based on merit.

Job Summary

We are searching for a seasoned Data Modeller skilled in Erwin Data Modeler, Azure data technologies, PySpark, and SQL. The successful candidate will translate intricate business needs into robust conceptual, logical, and physical data models tailored for enterprise data platforms including data warehouses, lakehouses, analytics, and reporting systems. This role demands collaboration with business teams, data architects, engineers, analysts, and governance personnel to deliver standardized, secure, performance-optimized, and reusable data structures.

Responsibilities

• Design and develop conceptual, logical, and physical data models for operational, analytical, data warehouse, and lakehouse environments.
• Create entity-relationship, dimensional, domain, and physical database designs using Erwin Data Modeler following standardized naming and subject-area conventions.
• Convert business requirements, data exploration, and source system schemas into clear entities, attributes, relationships, keys, hierarchies, and business rules.
• Build normalized, denormalized, dimensional, Data Vault, and domain-focused models depending on solution needs and data consumption patterns.
• Define fact and dimension tables, determine data grains, measures, surrogate keys, conformed dimensions, hierarchies, and implement slowly changing dimension strategies.
• Develop and update source-to-target mappings, maintain data dictionaries, metadata, transformation rules, business glossaries, and comprehensive model documentation.
• Conduct data profiling, reverse engineering, impact analysis using SQL and PySpark on large structured and semi-structured datasets.
• Collaborate with data engineers to deploy models on Azure Synapse Analytics, Azure Databricks, Azure SQL Database, Azure Data Lake Storage Gen2, Delta Lake, and allied Azure services.
• Design efficient schema structures including partitioning, file layouts, indexing, data types, and storage tactics to optimize performance, scalability, and cost-efficiency.
• Validate model implementations through complex SQL queries, PySpark notebooks, data reconciliation, and quality controls.
• Audit transformation logic and ETL/ELT workflows to ensure consistency with data model standards and source-to-target tracking.
• Oversee version control, schema evolution, dependencies, and assess impacts across connected upstream and downstream processes.
• Contribute to enterprise metadata management, data lineage, classification, governance, security, privacy, and retention protocols.
• Lead modeling workshops and design reviews engaging architects, analysts, product owners, engineers, and business experts.
• Support testing, resolve defects, assist in production issues, enhance performance, fulfill audit requirements, and continuously improve data models.
• Promote best practices including standardized data modeling conventions, reusable patterns, and proper documentation.

Required Experience and Skills

• A minimum of 8 to 15 years of IT experience, with at least 5 years focused on data modeling, architecture, analytics engineering, or enterprise data management.
• At least 3 years of practical experience with Erwin Data Modeler in large-scale enterprise settings.
• Demonstrated success delivering Azure cloud-based data warehouse, lakehouse, analytics, migration, or modernization initiatives.
• Proven ability to design models for extensive datasets and support implementation using SQL, PySpark, and Azure technology stacks.

Benefits

• Work with industry experts and stay abreast of evolving technology trends.
• Career growth through innovative roles and educational opportunities.
• Comprehensive training programs to keep skills current alongside competitive compensation, health benefits, and wellness initiatives to support future planning.