You will construct optimized star-schema dimensional models with proper fact and dimension table structures, implementing surrogate keys and design patterns that maximize query performance for analytical workloads.

You will develop standardized semantic metrics layers that ensure consistent business logic across analytics platforms, eliminate metric drift, and provide a unified source of truth for enterprise reporting.

You will implement advanced partitioning and clustering techniques using SQL DDL commands to optimize query performance for large-scale datasets.

You will evaluate database normalization levels against query performance requirements to make strategic denormalization decisions for optimizing analytical workloads.

You will design and document comprehensive Entity-Relationship diagrams that effectively communicate complex data structures and relationships for enterprise data systems.

You will build automated SCD Type 2 pipelines using MERGE statements and window functions to preserve historical data integrity in enterprise environments.

You will conduct comprehensive cost analysis of data lifecycle patterns to develop strategic archiving recommendations that balance storage economics with business value.

You will design scalable multi-cluster data warehouse architectures that isolate workloads for optimal performance while implementing comprehensive cost control and resource management policies.

You will learn the technical implementation of external table configurations to enable direct querying of file-based datasets in cloud storage.

You will develop analytical frameworks to evaluate and compare the technical capabilities of Delta Lake, Apache Iceberg, and Apache Hudi for specific business requirements.

You will architect and implement automated data ingestion pipelines that orchestrate data movement across medallion architecture zones within lakehouse platforms.

You will design and implement a comprehensive data lakehouse architecture that integrates dimensional modeling, schema optimization, cost management, and multi-format data ingestion. This project synthesizes advanced SQL skills to create a production-ready data engineering solution.