Senior Forward Deployed Engineer (Technical Data Architect)

databricks·Londonsenior

In short

→Arquitecto técnico que entrega soluciones de datos y IA en clientes reales.
→Trabajas con equipos del cliente, diseñando arquitecturas escalables y seguras en la nube, usando Spark y ML.
→Puedes influir en la evolución del producto Databricks con soluciones reutilizables.

Fluent written and spoken English required

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What they ask for

✓Experiencia en ingeniería de datos, plataformas de datos o desarrollo full stack
✓Capacidad para escribir código en Python, Scala, JavaScript/TypeScript
✓Conocimiento de al menos dos nubes (AWS, Azure, GCP), con expertise en una
✓Experiencia profunda con Apache Spark™ y sus internos del runtime
✓Familiaridad con CI/CD para despliegues en producción
✓Experiencia en diseño e implementación de arquitecturas de datos y ML/AI de alto rendimiento

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PythonScalaJavaScriptTypeScriptAWSAzureGCPApache Spark™CI/CDMLOps

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Req ID: CSQ427R156 Location: London, United Kingdom - Hybrid Job Role: Senior Forward Deployed Engineer - Technical Architect level Recruiter: Dina Hussain We’re hiring for multiple roles within our FDE team. 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 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 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 that lead to a customer's 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 customers' 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: • Experience in data engineering, data platforms & analytics, or software engineering / full stack development • Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks • Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one • Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals • 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

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