Data Modeler Engineer

Job Description Total Required Experience in Years: Minimum 810+ YearsRead on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.Mode of Work: Onsite (No Remote)Job Description:Seeking an experienced Data Modeler Engineer to design and implement enterprise-grade data models supporting large-scale Snowflake and Data Warehouse modernization initiatives within a banking environment. The ideal candidate should possess strong expertise in data modeling, Snowflake architecture, SQL, ETL concepts, ER modeling, SAS data analysis understanding, and enterprise data warehousing. This role requires hands-on experience designing logical and physical data models, supporting Snowflake architecture, building scalable enterprise data warehouse schemas, optimizing data structures for performance, and ensuring data quality, governance, and metadata management while aligning technical solutions with business requirements.Key Responsibilities:Design and implement enterprise logical and physical data models for scalable data platformsDefine enterprise data modeling standards, structures, and best practices supporting Snowflake environmentsConduct impact analysis and ensure model alignment with business and reporting requirementsEngineer conceptual, logical, and physical ER models for enterprise-grade data platformsDesign high-performance data warehouse schemas including Star and Snowflake schemas for analytics optimizationDevelop and optimize Fact and Dimension tables supporting reporting and BI workloadsApply dimensional modeling techniques including Kimball methodology and Data Vault 2.0 architectureSupport Snowflake data modeling, clustering, query optimization, and performance tuning activitiesUtilize advanced SQL for data transformation, validation, and query optimizationCollaborate with ETL teams to design scalable and efficient enterprise data pipelinesEnsure enterprise data integrity, governance, metadata management, and data quality standardsTranslate business requirements into scalable, future-ready enterprise data modelsDesign end-to-end Data Warehouse architecture across staging, core, and presentation/BI layersAdditional Responsibilities:Support enterprise modernization and data warehouse optimization initiativesCollaborate with business teams, architects, ETL developers, and stakeholders on enterprise data strategiesMaintain enterprise modeling documentation, standards, and governance practicesSupport performance tuning and scalable data platform improvementsEnsure alignment between business needs, enterprise architecture, and reporting requirementsRequired Skills:Strong expertise in enterprise data modeling and ER modeling conceptsStrong Snowflake experience including architecture, clustering, and performance tuningAdvanced SQL skills supporting transformations, validations, and query optimization xmcpwfuStrong understanding of SAS for data analysis and business logic interpretationExperience with ETL concepts, Data Warehousing, and scalable data pipeline designExperience designing Star and Snowflake schemas for reporting and analytics workloadsExpertise in Dimensional Modeling (Kimball) and Data Vault 2.0 methodologiesStrong experience developing Fact and Dimension tables for enterprise reporting systemsExperience supporting enterprise data governance, integrity, and metadata managementQualifications:Minimum 810+ years of strong hands-on Data Modeling and Data Warehouse experience requiredExperience supporting Snowflake modernization and enterprise analytics initiatives preferredStrong enterprise architecture, performance optimization, and stakeholder collaboration experience preferredExperience translating business requirements into scalable enterprise data solutions preferred