Sr. Forward Deployed Engineer - Financial Services

Databricks Databricks · Data AI · CA · Remote · Professional Services Operations

Sr. Forward Deployed Engineer at Databricks focused on building and productionizing AI/ML solutions for financial services customers using the Databricks platform. The role involves owning architecture, leading design, and implementing end-to-end systems spanning data engineering and AI.

What you'd actually do

  1. 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
  2. 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.
  3. Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  4. Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  5. 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.

Skills

Required

  • 6+ years experience in data engineering, data platforms & analytics, or software engineering
  • Python, Scala, JavaScript/TypeScript, and modern frameworks
  • AWS, Azure, GCP
  • Apache Spark™
  • CI/CD for production deployments
  • 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.
  • 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.

Nice to have

  • Databricks Certification

What the JD emphasized

  • production-grade systems
  • ML/AI model integration
  • end-to-end design
  • build and deployment
  • ML/AI models
  • production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.

Other signals

  • customer-facing role
  • productionize solutions
  • end-to-end systems
  • ML/AI model integration
  • Databricks platform