Description

Key Responsibilities 

Enterprise Lakehouse Data Modeling 

·       Define canonical business entities, relationships, hierarchies, reference data, and business rules. 

·       Design conceptual, logical, and physical data models optimized for Databricks Lakehouse architecture. 

·       Design analytical models optimized for BI, AI/ML, self-service analytics, and operational reporting. 

·       Develop enterprise data models supporting Bronze, Silver, and Gold data layers. 

·       Develop data models that align with organizational domains while maintaining enterprise data consistency. 

·       Model structured, semi-structured, and complex nested data sources. 

·       Create reusable data products that can be consumed across multiple business domains. 

·       Partner with business and technical domain owners to design trusted, reusable enterprise data assets. 

·       Adopt and propose modeling standards to govern data products that support analytics, operational reporting, AI/ML, and self-service consumption. 

·       Establish reusable business entities, reference data structures, and semantic definitions that can be leveraged across multiple use cases. 

·       Establish data contracts for data sharing and interoperability across business functions as well as external partners.  

·       Collaborate with governance teams to ensure data products are discoverable, well-documented, and governed through Unity Catalog. 

·       Support scalable ownership models where business domains are accountable for the quality and stewardship of their data assets. 

·       Design and participate in the development of data engineering pipelines for silver and gold data models. 

Preferred Experience (Priority Order) 

·       5+ years of enterprise data modeling experience.  

·       3+ years of Databricks Lakehouse modeling experience. 

·       Experience designing Silver-layer enterprise data assets that serve as authoritative enterprise assets. 

·       Experience developing curated Gold-layer data products for executive reporting, operational analytics, and AI use cases. 

·       Knowledge of Delta Lake, Unity Catalog governance, lineage, tagging, and metadata management. 

·       Experience with Open Data Formats such as Delta Lake, Apache Iceberg, or Apache Parquet. 

·       Experience modeling for event-driven, streaming, and near real-time architectures. 

·       Familiarity with Data Contracts and schema evolution management. 

·       Understanding of data products and domain-owned data architecture patterns. 

·       Experience supporting AI, GenAI, and machine learning workloads within a Lakehouse environment. 

·       Knowledge of Liquid Clustering and DBX Unity Catalog Predictive Optimization strategies to optimize large-scale Delta tables and modern Lakehouse optimization techniques

Key Skills

Education

Bachelor's degree