Sr. Forward Deployed Engineer

Databricks

Posted 27d ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

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
Work with engagement managers to scope technical delivery work with input from the customer
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
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
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

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
Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
Travel to customers 20% of the time

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
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

Skills