Data Modeler

You should have familiarity with modern storage formats like Parquet and ORC. Your responsibilities will include designing and developing conceptual, logical, and physical data models to support enterprise data initiatives. You will build, maintain, and optimize data models within Databricks Unity Catalog, developing efficient data structures using Delta Lake to optimize performance, scalability, and reusability. Collaboration with data engineers, architects, analysts, and stakeholders is essential to ensure data model alignment with ingestion pipelines and business goals. You will translate business and reporting requirements into a robust data architecture using best practices in data warehousing and Lakehouse design. Additionally, maintaining comprehensive metadata artifacts such as data dictionaries, data lineage, and modeling documentation is crucial. Enforcing and supporting data governance, data quality, and security protocols across data ecosystems will be part of your role. You will continuously evaluate and improve modeling processes. The ideal candidate will have 10+ years of hands-on experience in data modeling in Big Data environments. Expertise in OLTP, OLAP, dimensional modeling, and enterprise data warehouse practices is required. Proficiency in modeling methodologies including Kimball, Inmon, and Data Vault is expected. Hands-on experience with modeling tools like ER/Studio, ERwin, PowerDesigner, SQLDBM, dbt, or Lucidchart is preferred. Proven experience in Databricks with Unity Catalog and Delta Lake is necessary, along with a strong command of SQL and Apache Spark for querying and transformation. Experience with the Azure Data Platform, including Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database is beneficial. Exposure to Azure Purview or similar data cataloging tools is a plus. Strong communication and documentation skills are required, with the ability to work in cross-functional agile environments. Qualifications for this role include a Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field. Certifications such as Microsoft DP-203: Data Engineering on Microsoft Azure are desirable. Experience working in agile/scrum environments and exposure to enterprise data security and regulatory compliance frameworks (e.g., GDPR, HIPAA) are also advantageous.,