• Define and implement modern data warehouse architecture and frameworks, covering data modeling, ETL pipelines, orchestration, storage, and access patterns • Develop scalable data solutions leveraging Databricks, AWS, and other modern tools to handle large-scale, high-frequency data workloads • Design and build APIs and data integration layers to enable interoperability across systems and real-time data access • Continuously improve performance, scalability, and cost efficiency across ETL processes, compute environments, and data delivery systems • Work with cross-functional teams—including Data Engineering, Platform Engineering, and Analytics—to align technical solutions with business outcomes • Champion best practices for data quality, lineage, metadata management, and compliance • Create architecture diagrams, technical documentation, and design templates to support reuse and consistency across the organization