CSQ227R36

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, and other technical needs to help 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 data 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 know how to complete projects according to specifications with exceptional customer empathy.

The impact you will have:

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom data applications and data ingestion and ML/AI model integration
Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading Big Data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues.
Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

6+ years of experience in data engineering, data platforms & analytics, (additional software engineering experience is a nice-to-have)
Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
Familiarity with CI/CD for production deployments
Working knowledge of MLOps, ML/AI models and AI APIs
Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
Documentation and white-boarding skills.
Experience working with enterprise clients and managing conflicts across a broad stakeholder range
Build skills in technical areas, and demonstrate curiosity, adaptabil