Espen Brandt-kjelsen
Solution Engineer at Microsoft
Oslo, Norway
Summary
🤩
Rockstar🎓
Top SchoolEspen Brandt-kjelsen is a seasoned solution engineer and data architect with two decades of IT experience and a decade focused on cloud, AI, and advanced analytics at Microsoft. He has led large-scale data transformations and cloud adoption programs, designing scalable, secure Azure architectures for industries including Oil & Gas, Retail, Manufacturing, Travel and Energy. Equally comfortable as a hands-on architect and a people leader, he mentors teams to turn complex data challenges into practical, production-ready solutions. His background spans BI, ETL, OLAP, and machine learning, reflecting deep expertise from SQL Server-era data platforms to modern Big Data and ML pipelines. Based in Oslo, he thrives in ambiguous environments and is known for combining technical clarity with empathy to deliver resilient enterprise systems. An understated strength is his long-running ability to bridge product, sales and engineering perspectives—helping organizations both adopt and operationalize AI.
10 years of coding experience
16 years of employment as a software developer
Master of Applied Computer Science, Information Technology, Master of Applied Computer Science, Information Technology at Westerdals Oslo ACTBachelor, Information Systems., Bachelor, Information Systems. at The Norwegian School of Information Technology
English
Github Skills (37)
architecture10
reference-implementation10
azure-policy10
design-principles10
landing-zone10
scale10
aws10
data-product10
arm10
azure10
terraform9
large-scale9
data-mesh9
data-platform9
azure-functions9
Programming languages (5)
Github contributions (5)
esbran/CatHealthAPI
Aug 2021 - Sep 2021
Contributions:12 commits, 7 pushes in 12 days
esbran/data-product-analytics
Jan 2022 - Apr 2022
Template to deploy a Data Product for analytics and data science use-cases into a Data Landing Zone of the Data Management & Analytics Scenario (former Enterprise-Scale Analytics). The Data Product template can be used by cross-functional teams to create insights and products for external users.
Contributions:19 pushes in 2 months
casesanalyticsdata-managementdata-productscience
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