As a Forward Deployed Engineer at Databricks, you will work closely with customers to develop and implement solutions for their data and AI challenges using the Databricks platform. This hands-on, customer-facing role requires a blend of engineering expertise and business acumen to deliver impactful projects. You will lead architecture and design decisions while collaborating with various teams to ensure successful project delivery. The ideal candidate is adaptable, curious, and passionate about solving complex problems that drive measurable outcomes.

• 6+ years of experience in data engineering, data platforms & analytics, or software engineering.
• Proficiency in writing code in 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.
• Experience with technical project delivery, managing scope, timelines, and measurable outcomes.
• Strong documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Databricks Certification.

• Lead impactful customer technical projects by delivering production-grade systems and designing reference architectures.
• Guide strategic customers in implementing transformational big data projects from design to deployment.
• Advise customers on architecture and design to ensure successful understanding and adoption of Databricks.
• Collaborate with the Databricks technical team and customer teams to meet engagement needs.
• Provide product and implementation feedback to Engineering and Customer Support for rapid issue resolution.
• Engage with customer stakeholders to deeply understand challenges and deliver impactful solutions.
• Contribute to the development of reusable assets, frameworks, and best practices to scale impact across accounts.