(Junior) Software Engineer or Systems Architect for a data analysis and visualisation service
Our group
The service unit Future IT – Research & Education (FIRE) at the Heidelberg University Computing Centre (URZ) is a dedicated young team at Germany‘s oldest university. We map the boundaries of technology in order to enable scientists to deliver the world-class research our university is known for. Our organisation encourages us to learn and cultivate a sharing culture through teamwork, regular talks and open-source contributions. All team members are given the possibility to pursue their own research goals or attend field-specific conferences. Close collaboration and shared goals connect us with other computing centres and research labs in the federal state of Baden-Württemberg, Germany.
Our project
Research is more and more data-driven, with a rapidly growing amount of large sets of 3D data, which creates a demand for interactive remote visualisation. The service we create will allow scientists to efficiently analyse data. It is unique in that it is focused on a scalable container-first cloud platform, specifically targeted at the visualisation needs of researchers in Baden-Württemberg. We lower the entry barrier by focusing on usability and a user-friendly web frontend, provide building blocks for bringing custom user-specific tools onto our platform and encourage sharing within the community by promoting open source and open data.
You will
  • develop a web application to provide user-friendly control of compute jobs

  • improve the backend with regard to scheduling algorithms, resource management and hardware virtualisation

  • support and train users, especially with regard to the usage and creation of containerbased visualisation applications

  • automate functional / integration tests of the container-based remote visualisation applications and compliance to security regulations

  • assist in the maintenance of high-performance computing clusters, storage systems for scientific data, and the data analysis and visualisation platform itself

  • contribute to scientific projects in the area of data-intensive computing (e.g. design and realisation of test setups)

You are
  • eager to work with users to develop tailor-made and user-friendly solutions

  • curious to get to know new techniques and technologies

  • at home on the Linux command line and in the Linux ecosystem in general

  • experienced in at least two programming paradigms (e.g. imperative and functional)

  • familiar with agile methods, hammock-driven development (HDD) and continuous integration and deployment (CI/CD)

  • active in the free/libre open-source community through bug reports, documentation or source code contributions

You might already have some experience with
  • operating-system-level virtualisation (e.g. Docker or CRI-O) and container orchestration (e.g. Kubernetes and Helm)

  • platform virtualisation (e.g. KVM/QEMU) and cloud management (e.g. OpenStack)

  • Clojure/ClojureScript, Reagent (React), re-frame (SPA), Pedestal and Lacinia (GraphQL) and related technologies

  • security hardening of infrastructure and containers

This full-time position is to be filled as soon as possible. The employment is limited to a duration of three years. You will be paid according to TV-L regulations. Part-time employment can be negotiated.
Please send your application (portfolio links, motivation letter and resumé) in English, if possible as a single PDF file via e-mail, with the subject “Data Analysis Service” to the Heidelberg University Computing Centre, Future IT – Research & Education (FIRE), Dr. Martin Baumann, Im Neuenheimer Feld 293, 69120 Heidelberg, e-mail: bewerbung@urz.uniheidelberg.de. The application deadline is 26 March 2018.
Should you send in a physical application, please understand that none of the application documents submitted will be returned.
Heidelberg University aims to increase the number of women in those areas in which women are underrepresented. Thus, we specifically ask qualified women to apply for this position.
Preference will be given to equally qualified applicants with severe disabilities.