10+ years of overall experience in Data Modeling, Data Architecture, Data Warehousing, and Enterprise Data Management.
Proven expertise in designing conceptual, logical, and physical data models for large-scale enterprise platforms.
Strong experience with Data Vault 2.0, Dimensional Modeling, Kimball Methodology, Star/Snowflake Schemas, and 3NF Modeling.
Hands-on experience with industry-standard modeling tools such as ERwin Data Modeler, ER/Studio, PowerDesigner, or SQL Developer Data Modeler.
Experience working with modern data platforms including Snowflake, Azure Synapse Analytics, Microsoft Fabric, Databricks, SQL Server, Oracle, PostgreSQL, MongoDB, and Cassandra.
Strong understanding of AI/ML data foundations, including data preparation for Machine Learning, Generative AI, RAG architectures, Knowledge Graphs, Vector Databases, Feature Engineering, and AI Data Governance.
Experience designing AI-ready data ecosystems that support advanced analytics, predictive modeling, and LLM-based solutions.
Hands-on experience with cloud technologies such as Microsoft Azure, Azure Data Factory, Azure Databricks, Azure OpenAI, AWS, and GCP.
Proficiency in SQL, Python, PySpark, and Spark SQL for data modeling, transformation, and analytics workloads.
Strong knowledge of data governance, metadata management, data lineage, master data management (MDM), data quality frameworks, security, and regulatory compliance.
Experience collaborating with Data Architects, Data Engineers, AI/ML Engineers, Business Analysts, and Product Owners in enterprise environments.
Excellent analytical, communication, and stakeholder management skills with the ability to translate business requirements into scalable data solutions.
