Sr. Forward Deployed Engineer - FDE (Data and AI Architect, SAP & Databricks)

CSQ427R34 As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training teams, and meeting other technical needs so customers get the most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and deliver projects on scope, on time, and with measurable results. Why SAP expertise is at the core of this role: Many of our largest customers run their business on SAP, and most are now deciding how to modernize their SAP BW landscapes and unlock SAP data for AI. You bring deep SAP Business Warehouse experience (BW 7.x, BW on HANA, BW/4HANA) and a solid understanding of S/4HANA and ECC. With Databricks, you will help customers migrate or integrate those landscapes with the Lakehouse, preserve the business semantics built up over years, and turn SAP data into AI and applications that deliver real business value. The impact you will have Production Solution Delivery: Lead customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, data ingestion pipelines, and ML/AI model integrations. Strategic Customer Projects: Guide strategic customers through large-scale data and AI initiatives, from end-to-end design to build and deployment. Work with engagement managers to scope technical delivery with input from the customer. Empower Customers: Guide customers on architecture and design, and bootstrap or implement projects that lead to their successful evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices. Collaborate to Deliver: Work with the Databricks technical team, Project Manager, Architect, and customer team to ensure the technical components of each engagement meet the customer's needs. Close the Feedback Loop: Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to resolve engagement-specific issues quickly. Customer Immersion: Embed with customer teams and engage stakeholders from technical ICs to executives to deeply understand their challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. In your SAP engagements, you will also: Lead SAP modernization and migration to Databricks: Assess existing BW estates (data flows, InfoProviders, CompositeProviders, process chains) and define rebuild, retire, or keep strategies for moving to the Lakehouse. Design SAP data integration: Build ingestion patterns for SAP sources (ODP/ODQ, CDS views, SLT, Datasphere replication flows and Open Sharing via SAP Business Data Cloud connect) into Lakehouse. Preserve business semantics: Rebuild hierarchies, authorizations, currency/unit conversions, and key figures in Unity Catalog and metric views so analysts keep trusted definitions. Architect hybrid and coexistence models: Advise on patterns where SAP Datasphere and Databricks work side by side rather than assuming rip-and-replace. Build AI and applications on SAP data: Deliver use cases such as forecasting, working capital, supply chain and procurement analytics, and GenAI applications over ERP data, including user-facing interfaces.