Join EY as a Senior Manager and a seasoned Databricks Architect within our AI and Data team. You will be instrumental in leading complex data, analytics, cloud, and AI transformation initiatives. This role offers a unique opportunity to blend delivery governance, commercial acumen, and architectural oversight to craft scalable, secure, and cost-effective data solutions. You will be the key architect defining target-state architectures, engineering standards, and governance frameworks, ensuring alignment with business objectives and AI strategies. Move seamlessly between executive-level discussions, program management, and intricate solution design.

Lead comprehensive data and analytics programs from inception to successful realization, establishing robust governance, delivery cadences, and executive reporting. Manage all aspects of program delivery, including scope, budget, risks, and quality, ensuring proactive intervention when deviations occur. Drive agile or hybrid delivery methodologies tailored to client needs. Architect modern, cloud-native data platforms including data lakes, lakehouses, warehouses, and streaming solutions. Develop enterprise data strategies, define target architectures, and create prioritized transformation roadmaps. Guide data modeling, integration patterns, and platform evaluations, providing architecture assurance throughout the delivery lifecycle. Establish comprehensive data governance principles and embed robust controls for quality, privacy, and security.

We are seeking a candidate with a Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field, possessing at least 15 years of technology experience. A significant portion of this experience should be in delivering enterprise data programs and in a lead data or solution architecture capacity. Proven experience in designing and implementing cloud data platforms on Azure, AWS, or Google Cloud is essential, with deep expertise in at least one. Proficiency with modern data technologies such as Microsoft Fabric, Databricks, Synapse Analytics, Snowflake, Spark, and Kafka is required. Advanced SQL and a strong understanding of Python or PySpark, data integration, distributed processing, DevOps, CI/CD, and observability are crucial. Solid command of data modeling, metadata management, data quality, governance, privacy, and security principles is expected. Experience architecting AI-ready data foundations and integrating ML/GenAI capabilities is desirable.