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 (Machine Learning) @ kyndryl

ES | 2025-12-28
A data scientist role at Kyndryl's AI Agentic Innovation Hub involves designing and validating machine learning models across the entire lifecycle, with the notable differentiator being its focus... read more »
Go, AI/ML, Data Science, Data Collection, MLOps, Cloud Computing, Analytics, Python, Pandas, NumPy, Matplotlib, TensorFlow, PyTorch, Azure, Amazon SageMaker, Databricks, PhD, NLP, DataViz, BI, Agile/Scrum, Microsoft
data scientist

Manager - Data & AI @ ernstandyoung

ES | 2025-12-26
EY’s Data & AI Manager role asks you to lead end-to-end data transformations for top clients, shape cloud architectures on Azure and Databricks, and turn strategy into measurable value through... read more »
AI/ML, Cloud Computing, Azure, Databricks, Data Science, Power BI, Agile/Scrum, Synapse, Fabric, Kafka, MLOps, Microsoft
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.

Learn More
data scientist

Data Scientist @ easports

ES | 2025-12-26
EA’s Sports Security Data role in Madrid places a data scientist at the heart of fair play: turn game-behavior data into automated alerts, metrics, and models that detect fraud and anomalous... read more »
AI/ML, Analytics, SQL, NoSQL, Python, DataViz, Tableau, Looker, Matplotlib, Big Data, Hadoop, Spark, Splunk, Cloud Computing, AWS, GCP, Azure, Data Engineering
data scientist

Consultor/a Senior - AI Engineer @ kpmg-espana

ES | 2025-12-26
Senior AI Developer at KPMG Lighthouse in Madrid, tasked with building generative AI solutions from architecture to production and stitching language models into enterprise systems. The role... read more »
Analytics, AI/ML, LLM, Cloud Computing, MLOps, Python, API, PyTorch, TensorFlow, Azure, AWS, GCP