Join EY's GDS Consulting team as a Senior Manager, specializing in AI and Data with a focus on Databricks. This role offers a unique opportunity to build a fulfilling career within a global, inclusive, and technologically advanced environment. You'll contribute to shaping the future of our clients' businesses by leveraging deep industry experience and robust technical capabilities.

Our Data and Analytics team within EY Consulting tackles complex challenges and seizes opportunities to drive better business outcomes. We empower clients by embedding advanced analytical practices into their core decision-making processes, creating a compelling business case for data-driven strategies.

Architect and implement scalable Data & AI solutions on the Databricks Lakehouse platform, managing ingestion, transformation, storage, governance, and consumption. Design and optimize large-scale distributed data processing pipelines using Hadoop, Apache Spark, and PySpark. Develop production-grade Python frameworks for batch and streaming workloads. Define and implement cloud data architectures on AWS and/or Azure, ensuring seamless Databricks integration. Own end-to-end ETL/ELT processes, data ingestion, transformation, orchestration, and data quality frameworks. Design dimensional data models to support analytical and reporting needs.

Build Agentic AI solutions, including LLM integration, tool/function calling, and agent workflows. Architect and implement RAG solutions on Databricks, covering document ingestion, embeddings, vector search, and retrieval. Establish and enforce engineering best practices for Git, code reviews, and CI/CD. Lead performance optimization and production deployment of Databricks jobs. Participate in strategic RFP/RFI responses and client proposal development. Act as a technical advisor, translating business needs into robust technical architectures. Mentor engineering teams on Databricks, Spark, cloud architecture, and AI/RAG practices.

A seasoned Data & AI Architect with over 13 years of experience in data engineering and architecture, possessing strong hands-on expertise in Databricks, Hadoop, Spark/PySpark, and cloud data platforms. The role demands proficiency in designing enterprise Lakehouse and data platform architectures, alongside practical experience in building Agentic AI and RAG solutions on Databricks. You should be comfortable designing large-scale data pipelines, architecting AI-driven solutions, and engaging with clients on strategic proposals.

Key skills include deep expertise in Databricks Lakehouse, Delta Lake, Databricks SQL, and Unity Catalog, along with hands-on experience with Jobs/Workflows and performance optimization. Proficiency in the Hadoop ecosystem, HDFS, and Hive is essential. Strong hands-on experience with Apache Spark and PySpark for large-scale distributed data processing is required. You should possess strong Python skills for building scalable data pipelines and frameworks, coupled with extensive experience in AWS and/or Azure, including cloud storage, IAM, networking, and security. Expertise in ETL/ELT, batch and streaming processing, data ingestion, transformation, orchestration, and data quality is crucial. Strong SQL skills and experience in dimensional modeling are expected.

Furthermore, hands-on experience designing and building Agentic AI solutions and RAG solutions using Databricks is vital. Proficiency in Git, branching strategies, code reviews, and CI/CD pipelines is necessary. Experience with Databricks Asset Bundles or Terraform is a plus. The ability to participate in strategic RFP/RFI responses, shape solutions, develop technical proposals, and deliver architecture presentations is key. Excellent client-facing and communication skills are essential to translate business requirements into technical solutions for both technical and non-technical stakeholders.