Forward Deployed Engineer

Forward Deployed Engineer building and productionizing customer data and AI solutions on the Databricks platform. Own end-to-end architecture, implementation, and delivery of data pipelines, ML models, and applications while embedding with customer teams. Requires 5+ years in data/software engineering, Spark expertise, and multi-cloud knowledge.

About the job

Impact You Will Have

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, 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 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.
Collaboration: 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

5+ 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).