About the job
As a Sr. 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 most value out of their data.
Responsibilities
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; 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; Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks; 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; Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact; Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.
Qualifications
Minimum
6+ years experience in data engineering, data platforms & analytics, or software engineering; 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 - 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, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects; Travel to customers 20% of the time; Databricks Certification
Preferred
No preferred qualifications listed.