Data Modeller

About Cognizant

Cognizant is a major global provider of IT, consulting, and business process services, committed to helping leading companies worldwide strengthen their businesses. Headquartered in Teaneck, New Jersey, Cognizant is known for its client-driven passion, technological innovation, deep business expertise, and a diverse global workforce that shapes the future of work. The company is listed on NASDAQ-100, S&P 500, Forbes Global 2000, and Fortune 500, recognized as one of the fastest growing top-performing corporations globally.

Our Culture

At Cognizant, your passion, integrity, and experience are essential to our collective success. Joining our dynamic IT and consultancy team, you will be valued for your individuality and collaborative spirit. We pride ourselves on strong client partnerships, and your ability to deliver exceptional value and service is crucial. Opportunities to grow professionally and collaborate in a supportive, diverse setting await you.

We strongly promote a workplace that embraces multicultural diversity and gender equality, ensuring a merit-based, fair, and inclusive environment for all employees.

Job Summary

We are looking for a seasoned Data Modeller with hands-on expertise in Erwin Data Modeler, Azure data platforms, PySpark, and SQL. The successful candidate will transform complex business needs into robust conceptual, logical, and physical data models supporting enterprise platforms including data warehouses, lakehouses, analytics, and reporting systems. This role involves close coordination with stakeholders, architects, engineers, analysts, governance units, and data users to develop secure, reusable, standardized, and efficient data structures.

Responsibilities

• Create and maintain conceptual, logical, and physical data models for operational and analytical solutions including warehouses and lakehouses.
• Utilize Erwin Data Modeler to design entity-relationship, dimensional, domain, and subject-area models along with naming standards and physical database schemas.
• Convert business requirements, data insights, and source system frameworks into clear entities, attributes, and relationships following established standards.
• Architect normalized, denormalized, dimensional, Data Vault, and domain-focused models tailored to the specific solution and usage profiles.
• Define fact and dimension models, establish grain, measures, surrogate keys, hierarchies, conformed dimensions, and handle slowly changing dimension strategies.
• Develop and upkeep source-to-target mappings, metadata, data dictionaries, transformation rules, glossaries, and comprehensive documentation.
• Perform data profiling, discovery, reverse engineering, and impact analyses on large structured and semi-structured datasets using SQL and PySpark.
• Collaborate with data engineering teams to implement models on Azure Synapse Analytics, Databricks, SQL Database, Data Lake Storage Gen2, and Delta Lake services.
• Design schema, partitioning, file layouts, data types, indexing, and storage patterns to optimize performance, scalability, and cost efficiency.
• Validate model implementations through complex queries, PySpark notebooks, reconciliation, and data-quality verifications.
• Review ETL/ELT transformations to ensure alignment with data models and source-to-target specifications.
• Manage version control, schema evolution, documentation of changes, dependency analysis, and impact assessments.
• Support data governance including metadata management, data lineage, classification, privacy, retention, and security.
• Lead workshops and design reviews involving architects, analysts, product owners, engineers, and subject matter experts.
• Assist in testing, defect resolution, production troubleshooting, tuning, audits, and continual model enhancements.
• Promote enterprise data modeling standards, reusable design patterns, naming conventions, and documentation best practices.

Required Qualifications

• Between 8 to 15 years of IT experience, with at least 5 years dedicated to data modelling, data architecture, analytics engineering, or related enterprise data management.
• At least 3 years of hands-on work with Erwin Data Modeler in complex corporate settings.
• Demonstrated experience delivering Azure-based data warehouses, lakehouse solutions, analytics, and migration or modernization initiatives.
• Strong background in designing scalable models for large datasets and supporting implementations using SQL, PySpark, and Azure technologies.

Benefits

• Opportunity to collaborate with industry-leading professionals and stay at the forefront of emerging technologies.
• Access to career growth pathways and continuous professional development through training and education.
• Comprehensive compensation, benefits, and wellness packages aimed at supporting health and future planning.