Databricks13 дней назад

Forward Deployed Engineer

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РЫНОК

15 167 ₽медиана по профессии

Cloud Engineer · 40 вакансий с указанной зарплатой

5 233половина предложений: 9 708–18 66472 708

Работодатель не указал зарплату — сравните с рынком сами.

Berlin

Обязанности

01Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
02Guide 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
03Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
04Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices
05Work 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
06Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues
07Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact
08Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap

016+ years experience in data engineering, data platforms & analytics, or software engineering
02Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
03Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
04Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
05Familiarity with CI/CD for production deployments
06Working knowledge of MLOps, ML/AI models and AI APIs
07Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
08Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions
09Documentation and white-boarding skills
10Experience working with enterprise clients and managing conflicts across a broad stakeholder range
11Build 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
12Travel to customers 20% of the time
13Databricks Certification