Microsoft Azure

cloud, cloud provider, microsoft, infrastructure
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Microsoft, when the world moved to the cloud, didn't want to be left holding the on-premise bag. Thus emerged Azure, a platform promising to deliver everything-as-a-service with the comforting familiarity of Windows Server underneath. It aimed to be the enterprise’s easy transition, a way to lift-and-shift workloads without retraining entire departments. The reality, of course, is a bit messier. Azure is powerful, undeniably, but navigating its vast ecosystem can feel like exploring a Byzantine bureaucracy.

It’s essentially Amazon Web Services, but with a distinctly Microsoft flavor – meaning more integration with existing Microsoft products, and a pricing structure that requires a PhD in economics to decipher. While AWS still dominates, Azure has carved out a strong niche with enterprises already deeply invested in the Microsoft stack. Today, it's a mature platform, powering everything from simple websites to complex AI applications, and constantly battling AWS and Google Cloud for cloud supremacy – a battle fought largely in PowerPoint presentations and quarterly earnings reports.

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Jobs in using Microsoft Azure for but please no

data scientist

Data Scientist - Public Sector @ ibm

GB | 2025-12-27
A Senior Data Scientist role at IBM CIC involves leading AI solutions with a keen focus on foundation and large language models, offering the unique differentiator of embedded mentorship and... read more »
IBM, Cloud Computing, AI/ML, Data Science, Python, TensorFlow, PyTorch, AWS, Azure, GCP, GenAI, NoSQL, SQL, PostgreSQL, MongoDB, Linux
data scientist

Machine learning Scientist @ signify-technology

GB | 2025-12-26
Minimal company detail; the role calls for a Machine Learning Scientist to research, design, and deploy models to solve business problems, with emphasis on accuracy, efficiency, and scalability.... read more »
AI/ML, Analytics, Python, R, TensorFlow, PyTorch, Keras, Cloud Computing, AWS, GCP, Azure
promoted

O'Reilly: Building AI Agents with Model Context Protocol (MCP)

Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.

Get Started
data scientist

Data Platform Engineer @ webuild-ai

GB | 2025-12-26
WeBuild-AI seeks a Platform Engineer to craft scalable data solutions supporting AI transformations for global enterprises, with an emphasis on data architecture and cloud services. The role’s... read more »
AI/ML, AWS, Azure, Fabric, Data Governance, Data Quality, Redshift, AWS Glue, LLM, Synapse, Python, Cloud Computing, Data Modelling, Docker, Kubernetes, Vector DB, Pinecone, Neo4j, API, Data Streaming, Kinesis, Kafka, GitHub
data scientist

Senior Machine Learning Engineer - ML Infrastructure @ asos-com

GB | 2025-12-25
ASOS seeks a Senior Machine Learning Engineer to develop reusable templates, deployment patterns, and MLOps tooling aimed at standardizing ML workflows across the organization. The role emphasizes... read more »
AI/ML, MLOps, Marketing, CI/CD, Management, Data Engineering, Python, PyTorch, TensorFlow, Docker, Kubernetes, Cloud Computing, Azure, Spark, Databricks
data scientist

Data Scientist (England based) @ signify-technology

GB | 2025-12-25
The role seeks a data scientist with a focus on machine learning to drive business impact, but the description lacks specificity regarding the company’s culture, team dynamics, or technical depth... read more »
AI/ML, Python, R, SQL, Data Modelling, Cloud Computing, AWS, GCP, Azure
data scientist

Data Scientist @ london-stock-exchange-group

GB | 2025-12-24
LSEG seeks a seasoned Data Scientist with practical LLM Ops experience to help establish its inaugural LLM Ops capability, integrating AI system development, deployment, and performance... read more »
Data Science, AI/ML, Management, LLM, Git, CI/CD, Docker, Data Governance, Pandas, SQL, Python, GenAI, Cloud Computing, AWS, Azure, GCP, MLOps, Go
promoted

The Fundamentals of Analytics Engineering

The Fundamentals of Analytics Engineering gives a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering. It's a book that teaches concepts and best practices, not just tools and technologies.

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data scientist

Data Scientist @ myn-co-uk

GB | 2025-12-23
A data scientist role in London, focusing on predictive analytics, real-time dashboards, and collaboration across teams with big data tools like Spark, Hadoop, and Snowflake. The position's... read more »
AI/ML, Analytics, Python, R, SQL, Big Data, Spark, Hadoop, Snowflake, Data Science, Cloud Computing, AWS, GCP, Azure, NLP, GitHub