About me
With over a decade of experience rooted in scientific programming, I specialize in architecting scalable, data-intensive software solutions for the Norwegian tech sector. My expertise lies at the intersection of Cloud-Native Architecture, Advanced Data Engineering, and Machine Learning.
I bridge the gap between complex algorithmic challenges and production-grade software. From designing proprietary Master Data Management (MDM) platforms and Reverse ETL pipelines to engineering Computer Vision systems for infrastructure analysis, I build systems that turn raw data into strategic assets.
Core Architectural Focus:
- Cloud-Native Systems: Designing microservices and distributed systems on Azure, utilizing Kubernetes/Docker for orchestration and resilience.
- Data Engineering: Orchestrating high-throughput pipelines (Kafka, Event Hubs, Airflow) and modern data warehousing (Snowflake, Reverse ETL).
- Scientific Computing & AI: Implementing predictive maintenance models, geospatial analytics, and deep learning workflows (TensorFlow/Keras).
Technical Toolbox:
- Languages: Python (Expert), C#, JavaScript/TypeScript, Bash.
- Web: Django, FastAPI, Flask, ASP.NET.
- Data: Snowflake, Airflow, Kafka, Azure Event Hubs, CCloud, Azure Data Factory, Sesam, PostgreSQL, MongoDB
- Ops: Kubernetes, Docker, Azure, CI/CD, Linux.
I bridge the gap between complex algorithmic challenges and production-grade software. From designing proprietary Master Data Management (MDM) platforms and Reverse ETL pipelines to engineering Computer Vision systems for infrastructure analysis, I build systems that turn raw data into strategic assets.
Core Architectural Focus:
- Cloud-Native Systems: Designing microservices and distributed systems on Azure, utilizing Kubernetes/Docker for orchestration and resilience.
- Data Engineering: Orchestrating high-throughput pipelines (Kafka, Event Hubs, Airflow) and modern data warehousing (Snowflake, Reverse ETL).
- Scientific Computing & AI: Implementing predictive maintenance models, geospatial analytics, and deep learning workflows (TensorFlow/Keras).
Technical Toolbox:
- Languages: Python (Expert), C#, JavaScript/TypeScript, Bash.
- Web: Django, FastAPI, Flask, ASP.NET.
- Data: Snowflake, Airflow, Kafka, Azure Event Hubs, CCloud, Azure Data Factory, Sesam, PostgreSQL, MongoDB
- Ops: Kubernetes, Docker, Azure, CI/CD, Linux.
