Senior Forward Deployed Engineer - FDE

This customer-facing engineer designs, builds, and productionizes end-to-end data and AI solutions on the Databricks platform. The role requires 6+ years of engineering experience, cloud expertise, Apache Spark proficiency, and the ability to lead technical delivery with enterprise customers.

About the job

Responsibilities

Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
Guide strategic customers through the end-to-end design, build, and deployment of big data and AI applications.
Scope technical delivery work with engagement managers and customer input.
Guide customers on architecture and design, and bootstrap or implement projects to support successful understanding, evaluation, and adoption of Databricks.
Own architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
Collaborate with Databricks technical teams, project managers, architects, and customer teams to deliver technical components that meet customer needs.
Provide product and implementation feedback and help resolve engagement-specific product and support issues.
Embed with customer teams and engage stakeholders from technical individual contributors through executives.
Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Requirements

6+ years of experience in data engineering, data platforms and analytics, or software engineering.
Ability to write code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
Working knowledge of at least two cloud ecosystems, including AWS, Azure, and Google Cloud, with expertise in at least one.
Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
Familiarity with CI/CD for production deployments.
Working knowledge of MLOps, machine learning and artificial intelligence models, and AI APIs.
Experience designing and deploying performant, production-grade end-to-end data architectures and applications combining data pipelines, ML/AI models, and user-facing interfaces.
Experience delivering technical projects, managing scope and timelines, measuring outcomes, and translating complex concepts into actionable solutions.
Documentation and whiteboarding skills.
Experience working with enterprise clients and managing conflicts across diverse stakeholder groups.
Curiosity, adaptability, and eagerness to explore technologies supporting Databricks-based solution deployment and integration.
Willingness to travel to customers 20% of the time.
Databricks certification.