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Senior Forward Deployed Engineer (L5)

16 000 000 – 20 000 000 ₽в год
DatabricksIndiaУдалённоот 9 летПолная занятость
PythonSQLCI/CDTypeScriptJavaScriptAWSMachine LearningData EngineeringAzureGCPSparkScala

Описание

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. You will work with customers to build and productionize solutions to their data and AI challenges using the Databricks platform.

Responsibilities

  • 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

Requirements

  • 9+ years of 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