• Design and implement robust data architectures using Databricks, ensuring integration with existing systems and scalability for future growth • Establish data management frameworks, optimizing ETL/ELT processes and data models for performance and accuracy. • Evaluate and recommend modern architectural patterns, including Lakehouse, Delta Live Tables, Data Mesh, and real-time streaming. • Drive rapid Proof-of-Concepts (POCs) to validate new architectural approaches, tools, and design patterns before enterprise rollout. • Partner with data engineers, scientists, and business stakeholders to develop seamless data pipelines prioritizing data integrity and usability. • Implement and uphold data governance practices that enhance data accessibility while ensuring compliance with regulations. • Integrate external systems, APIs, and cloud-native services to support new data products and analytics use cases. • Prototype and test new connectors, ingestion frameworks, and integration patterns to accelerate innovation. • Monitor data pipelines and infrastructure performance, troubleshooting issues as they arise and ensuring high availability. • Optimize and enhance existing data systems for performance, reliability, and cost-efficiency. • Collaborate with data analysts and data scientists to understand data requirements and implement solutions that support data-driven insights and models. • Monitor and enhance system performance, employing tools and methodologies to optimize data processing and storage solutions. • Optimize compute costs, job orchestration, workflow efficiency, and data storage strategies. • Troubleshoot and resolve data-related issues to maintain optimal system functionality. • Experiment with new Databricks features (Unity Catalog updates, AI/ML runtimes, Photon, DBRX, Delta Sharing, serverless SQL/compute, etc.) through quick hands-on evaluations. • Develop and enforce data governance standards, including data quality, security, and compliance through automation. • Conduct fast-turnaround POCs to explore new technical capabilities, libraries, and features across Databricks, Azure, Informatica, Reltio, and other ecosystem tools. • Build lightweight demo pipelines, dashboards, and micro-solutions to demonstrate feasibility, guide architectural choices, and influence roadmap decisions. • Stay current with emerging technologies, industry trends, and platform advancements; translate insights into actionable recommendations. • Collaborate with vendors and internal teams to evaluate beta features, pilot new capabilities, and provide technical feedback for adoption decisions.