Enterprise Cloud Architect

6 hours ago

Kannur, Kerala, India beBeeArchitect Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Cloud Architect Leader

We are seeking a highly experienced Cloud Architect to lead the design and implementation of scalable, secure cloud solutions.

The ideal candidate will have a strong background in cloud-native architectures, data integration strategies, and DevOps practices. They should be proficient in at least one major cloud platform (e.g., AWS, Azure, Google Cloud) and multi-cloud strategies.

A bachelor's or master's degree in Computer Science, Engineering, or a related field is required, along with 10-12 years of experience in software architecture. The successful candidate will also have experience with AI/ML frameworks and the ability to integrate machine learning solutions into enterprise architectures.

In addition to their technical expertise, the Cloud Architect Leader should be an effective communicator, able to collaborate with cross-functional teams and drive initiatives forward.

Key Responsibilities:

  • Design and architect complex, scalable workflows and solutions that align with business needs.
  • Develop cloud-native architectures, ensuring scalability, performance, and security for enterprise applications.
  • Lead initiatives to improve data interoperability, enabling seamless integration of systems and efficient data exchange across diverse platforms.
  • Design and implement robust APIs, ensuring effective system integration, scalability, and data flow.
  • Advocate for and implement DevOps best practices, including CI/CD pipelines, infrastructure automation, and operational excellence.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 10-12 years of experience in software architecture, with expertise in cloud-native architectures and data integration strategies.
  • Strong experience in at least one major cloud platform (e.g., AWS, Azure, Google Cloud) and multi-cloud strategies.
  • Proficient in DevOps tools and practices (e.g., Docker, Kubernetes, Jenkins, Terraform) with a focus on automation and infrastructure-as-code.
  • Experience with AI/ML frameworks and the ability to integrate machine learning solutions into enterprise architectures.
  • Proven experience with data interoperability frameworks and tools, ensuring the seamless flow of data between different systems.

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