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6 месяцев назад

Senior Cloud Developer with Mathematical Background (Java)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Cloud Developer (Java): Building and optimizing cloud-native applications for data-driven geoscience using complex algorithms with an accent on microservices architecture, spatial data analysis, and distributed environments. Focus on integrating geostatistical models, ensuring scalability, and reliability of cloud systems.

Location: On Site in Texas, United States

Company

hirify.global is one of the world’s largest providers of products and services to the global energy industry.

What you will do

  • Design and develop cloud-native applications using microservices architecture, RESTful APIs, and containerization.
  • Implement and optimize complex algorithms for spatial data analysis and simulation in distributed cloud environments.
  • Collaborate with cross-functional teams to integrate geostatistical and mathematical models into scalable workflows.
  • Ensure code quality and maintainability through best practices, automated testing, and continuous integration.
  • Stay current with emerging cloud technologies to enhance system scalability and reliability.

Requirements

  • 10+ years of software development experience, with a strong focus on Java and cloud-based systems.
  • Bachelor’s degree or higher in Computer Science.
  • Background in Mathematics or a related technical field (Geosciences or Reservoir Engineering is a plus).
  • Proven expertise in Java development for microservices and API-driven architecture.
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), orchestration tools, and CI/CD pipelines.
  • Experience working in Agile environments with distributed scrum teams.
  • Strong communication skills and ability to work across time zones.

Nice to have

  • Familiarity with spatial statistics, variograms, and simulation techniques.
  • AI/ML work experience and machine learning technologies (Python, TensorFlow etc.).
  • Experience in Oil and Gas Domain.

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