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2 дня назад

Solution Engineer (SaaS)

Тип работы
fulltime
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Solution Engineer (SaaS/Data Cloud): Driving technical wins by designing and demonstrating hirify.global's data solutions to solve complex customer problems with an accent on data architecture and cloud technology. Focus on bridging the gap between business needs and technical implementation through PoCs and executive presentations.

Location: GB-London

Company

hirify.global is a leading data cloud company powering the era of the agentic enterprise.

What you will do

  • Present hirify.global’s technology and vision to executives and technical contributors at prospects and customers.
  • Lead the technical sales cycle from demonstrations to Proof of Concepts (PoC) and implementation design.
  • Develop technical champions within customer accounts to drive deals and achieve technical wins.
  • Maintain a deep understanding of the hirify.global roadmap and competitive landscape to position the product effectively.
  • Collaborate with Product Management, Engineering, and Marketing to continuously improve products and marketing.
  • Partner with ecosystem and implementation partners to build joint architectures and account strategies.

Requirements

  • Experience in solution engineering or solution architecture within a SaaS environment or relevant industry (analytics, data science, data engineering).
  • Proficiency in SQL and a strong understanding of data architecture, data analytics, and cloud technology.
  • Outstanding presentation skills for both technical and executive audiences.
  • Ability to translate complex business problems into technical solutions and communicate them effectively.
  • Must be based in or able to work from London, UK.

Nice to have

  • Experience in the Insurance industry.
  • Hands-on experience with Python.
  • Familiarity with modern data technology such as dbt, Spark, containers, DevOps tooling, orchestration tools, and Git.
  • Experience with AI, data science, and machine learning technologies.

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