Sr. Forward Deployed Engineer - FDE (Data and AI Architect, SAP & Databricks)
Databricks is hiring a Sr. Forward Deployed Engineer - FDE (Data and AI Architect, SAP & Databricks) in Berlin and Munich, Germany. Level rates it ; you can apply on Databricks.
Level's read on this job
- Level rates this forward deployed engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include MLOps.
- Level classifies it as a senior role.
- Level lists 895 other open roles at Databricks.
AI in this role
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.
What we look for
- 6+ years of experience in data engineering, data platforms & analytics, or software engineering
- Strong coding skills in Python, Scala, or JavaScript/TypeScript, and modern frameworks
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Deep experience with distributed computing using Apache Spark™ and knowledge of Spark runtime internals
- Hands-on experience with CI/CD for production deployments
- Working knowledge of MLOps, ML/AI models, and AI APIs
- Proven experience designing and deploying performant, production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
- Proven experience delivering technical projects: managing scope, timelines, and measurable outcomes, and translating complex concepts into actionable solutions
- Experience working with enterprise clients and managing competing priorities across a broad range of stakeholders
- Strong documentation and whiteboarding skills
- Hands-on experience with SAP BW across multiple versions (BW 7.x, BW on HANA, BW/4HANA), including data modeling (ADSOs, CompositeProviders, InfoObjects), BEx/Analysis for Office, and process chains
- Solid knowledge of SAP extraction technologies: ODP, SLT, CDS views, OData, and SAP HANA SQL/calculation views
- Comprehensive knowledge of S/4HANA and ECC data models
- Databricks Certification, or willingness to obtain it within [X] months of joining
- Willingness to travel to customers up to 20% of the time
- Curiosity, adaptability, and eagerness to explore new technologies that support Databricks-based customer solutions
- Bonus: Experience with SAP Datasphere (spaces, replication flows, data flows, Analytic Models) and/or SAP Business Data Cloud
- Bonus: Understanding of SAP functional domains (FI/CO, SD, MM, SCM) and how they surface in analytics
- Bonus: Familiarity with SAP NetWeaver, the ABAP stack, and Basis concepts
- Bonus: Experience leading BW-to-cloud migrations or SAP-to-Lakehouse integrations, including fit-gap and migration assessments
- Bonus: Experience working with SAP Basis, BW/BI, and functional teams, and navigating the organizational dynamics of evolving or retiring a long-standing BW estate
- Bonus: Ability to explain Lakehouse concepts to SAP-centric stakeholders (CIOs, SAP COE leads) using familiar BW terminology
Why join us
- Make a strategic impact on large, highly visible modernization programs at enterprises that run on SAP
- Combine your modeling and governance expertise with modern AI, streaming, and application development
- Contribute reusable accelerators and shape the product roadmap based on what you see in the field
- Work alongside engineering, product, and developer relations teams
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
How we rate this
Sr. Forward Deployed Engineer - FDE (Data and AI Architect, SAP & Databricks) at Databricks rates 78 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in forward deployed engineer jobs at this level
Pay
- Typical forward deployed engineer job
- $180k
This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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