Torbjörn Lundman

Torbjörn Lundman
Solution Architect
Råbyvägen 11
SE-7461 91
Bålsta
Sweden

OVERVIEW

Torbjörn has been working in the IT-industry since 1992. During the years I have developed broad and deep skills within different areas such as databases, data warehouses data integration/etl, data quality and business intelligence/data analytics solutions.

The last 15 years my focus has been to help customer/organizations how to get more out of their Information assets via different analytical and data management solutions. The last year I have been concentrating on implement solutions for Big Data (Data Lake/Hadoop) and how to integrate those new data types with existing data in the Data warehouse.

Torbjörn is very passionate in new technologies for enabling Big Data Analytics for the end users. As an example he is now educating (education and hackathon) he’s colleagues in how to implement end to end Big Data Analytics in the cloud Azure (Azure Data Lake for data store, Azure HDInsight for data processing, Zeppelin notebook(Spark Sql)/ Microsoft PowerBI for visualization)

Torbjörn is very customer focused and keen on delivering quality. His professional goal is to help customers to get more out of their information assets and to be an expert within the information management area.

Örebro University
1988-1991
Bachelor Of System Analysis Scientists
Skills
Data Architecture
Deep knowledge and experience on how to build modern data warehouse’s and big data advanced analytics plattform.
Architecture concepts
Deep understanding of architecture, concepts and technology for ingesting, storing, modelling and analyzing data.
Data Lake concepts
Hands-on experience with data lake (conceptutally and pracitcal implementation).
Data warehouse architecture and plattforms
Practical and hands-on experience on building large scale data warehouses with different technology plattforms.
Data Integration concepts
Extensive hands-on experience in designing and implementing etl-processes with different etl-tools.
Data modelling experience
Extenisive and strong knowledge in data modelling (data warehouse modeling and dimensional modelling) with methods like Data Vault and Kimball.
Communication skills
Strong in communicating technology with technical and non technical persons.,
Agile methods
Experience in working with agile methods such as scrum and kanban.