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Field
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focuses on cloud platform architecture, infrastructure automation, CI/CD processes, system integration, and operational reliability. This position supports the development and adoption of platform
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Department PSD Computer Science: Tech Administration About the Department The Department of Computer Science is an academic department that has a rich history of advancing and defining new fields
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autonomous, and better-informed decisions. As part of the University's data transformation programme, you will help develop and maintain cloud-based analytics solutions using Snowflake, dbt and modern data
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cloud and infrastructure services are designed, delivered and evolved across a newly integrated organisation. This is about creating the foundations — ensuring platforms are reliable, scalable, and ready
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including cloud computing, artificial intelligence, application development, enterprise integration, cybersecurity, and platform engineering. This position is a hybrid work arrangement and will work at least
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addition to the Minimum Qualifications above, the successful candidate must demonstrate hands-on experience in at least one of the following focus areas: Cloud computing — building, deploying, and managing solutions using
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down traditional academic silos, uniting domain experts from the life, physical, and social sciences, as well as the arts and humanities, with methodological leaders in computer science, statistics, and
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engineering, or a related technical field. Relevant certifications in DevOps and/or cloud engineering. Experience with infrastructure as code, automation, and cloud-based environments including tools such as
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(architecture, cost, governance) with product thinking (usability, self-service, adoption). A degree in Computer Science, Information Technology, or equivalent. At least 2–4 years of data infrastructure, platform
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, Alma Analytics, and other relevant systems. Evaluate new analytics tools, platform features, and data visualisation approaches for possible adoption. Apply emerging technologies, including AI workflows