SURFsara is looking for a technical consultant (advisor) with both technical and good communication skills to help deliver high-quality scalable services for researchers in The Netherlands. The Scalable Data Analytics group provides services related to data science and big data analytics and is continuously looking to improve its service offerings.
Working/thinking level: academic/vocational level
Number of hours: 38-40
In the SDA group we provide data analytics services to the Dutch academic community. Currently we use Kubernetes to deploy services, like JupyterHub and Apache Spark. The position of adviser entails setting up such services in close collaboration with system engineers, being responsible for service management and reaching out to new user communities.
In addition, the group is involved in several projects not necessarily related to the services mentioned above. These involve innovation projects and collaborations with other institutes. All these projects are somehow related to data analytics and data engineering.
You will work in a small, motivated, and innovative team that does quite a bit of multi-tasking. You will work with Kubernetes to deploy services like JupyterHub and Apache Spark. You will interact with (academic) users to explain how to best use these services and provide support. And you will participate or initiate new projects in which you will work on new developments in technology and data analytics.
A diverse work environment, with many nationalities (working languages are English and Dutch)
Send your motivation letter and resume to firstname.lastname@example.org.
You must be able to submit a Certificate of Good Conduct (Verklaring Omtrent Gedrag/VOG) during your first month of employment.Continue reading
|Title||Technical consultant distributed systems/big data|
|Job location||SURF Science Park, Science Park 140, 1098 XG Amsterdam|
|Published||September 26, 2019|
|Job types||Other  |
|Fields||Data Mining,   Data Structures,   Databases,   Distributed Computing,   Programming Languages,   Big Data  |