Data Modeler

13 hours ago

New Delhi, India Tezo Full time

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence.Data Modeler – Azure Data Engineering Location: Hyderabad Experience Level: 8–13 Years12+ yearsof experience in data management and data architecture, including5+ yearsfocused ondata modeling . Expertise indimensional modeling (Star/Snowflake) ,normalized models , anddata vault / data lake modeling . Strong experience withSQLandAzure Cloudecosystem — Azure Synapse, Data Factory, Data Lake, SQL DB, Databricks. Proven experience designing data models forenterprise data warehouses, data lakes, and analytics platforms . Experience working withbusiness glossary, metadata management, and data catalog tools(e.g., Purview, Collibra). Knowledge ofETL/ELT processes ,data pipelines , anddata integration patterns . Excellent communication, stakeholder management, and documentation skills.Key Responsibilities Data Modelling & Architecture Design, develop, and maintainconceptual, logical, and physical data modelsfor data warehouse, data lakehouse, and transactional systems. Implement and optimizedimensional models (star/snowflake)anddata vault/lakehouse modelsaligned with business needs. Define and enforcedata modeling standards , naming conventions, and metadata management practices. Collaborate with architects to define thedata architecture blueprint , ensuring scalability, governance, and performance. Cloud Data Engineering (Azure) Partner with Azure data engineers to implement data models using services such asAzure Data Lake, Azure Synapse Analytics, Azure SQL Database, Data Factory, and Databricks . Contribute to the design and optimization ofdata ingestion, transformation, and orchestration pipelinesin Azure. Participate indata governance ,master data management (MDM) , anddata quality initiatives . Collaboration & Stakeholder Engagement Work with business teams and data analysts to understand reporting and analytical requirements. Partner with enterprise architects to align modeling practices with data strategy and enterprise standards. Document data models, lineage, and definitions using enterprise metadata tools.

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