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Position: Computing Fellowship: DevOps Engineer
Institution: European Organization for Nuclear Research
Location: Genève, Switzerland
Duties: During this project, you will be involved in the migration of existing Jupyter extensions to JupyterLab (next-generation Jupyter notebook version) that are important for Spark and Hadoop users. These extensions are: 1) spark connector that allows connecting to the cluster without much prior knowledge on how to run and optimize Spark and 2) Spark monitor that allows visualizing the progress of currently running job
Requirements: You have graduated, or are about to graduate, with a university degree (BSc or MSc level in computer science, engineering or another relevant course) and have no more than 4 years’ relevant experience after obtaining your degree; Kindly note that experience prior to the latest obtained degree will not be taken into account for the calculation of your overall years of experience; You have experience in deploying and operating production-level service infrastructure under Linux platforms; You value learning and sharing knowledge with colleagues, following DevOps best practices; You are passionate about systems engineering building and evolving robust, secure, well-tested services and tools
   
Text: Computing Fellowship: DevOps Engineer Geneva, Switzerland Full-time Company Description At CERN, the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature. Find out more on http://home.cern. Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Job Description The context of this project is big data infrastructure evolution for operational use cases. Big data services in the IT-DB group are widely and increasingly being used in the NXCALS (Next CERN Accelerator Logging Service project, an essential element for operations of the LHC). You will be working in a team of big data engineers, and specifically in the evolution of the infrastructure and services dedicated for this project, both on the service part (Hadoop and Spark) and the user-facing analysis toolset (Jupyter notebooks) that offers simplified access to said infrastructure: SWAN service. You will be contributing in further implementing limits, controls and monitoring of user-defined jobs (both in Spark/Kubernetes and Spark/YARN) running in Hadoop. During this project, you will be involved in the migration of existing Jupyter extensions to JupyterLab (next-generation Jupyter notebook version) that are important for Spark and Hadoop users. These extensions are: 1) spark connector that allows connecting to the cluster without much prior knowledge on how to run and optimize Spark and 2) Spark monitor that allows visualizing the progress of currently running job. Qualifications Eligibility criteria: You are a national of a CERN Member or Associate Member State ; You have graduated, or are about to graduate, with a university degree (BSc or MSc level in computer science,engineering or another relevant course) and have no more than 4 years’ relevant experience after obtaining your degree; Kindly note that experience prior to the latest obtained degree will not be taken into account for the calculation of your overall years of experience. Essential skills and experience: You have experience in deploying and operating production-level service infrastructure under Linux platforms; You value learning and sharing knowledge with colleagues, following DevOps best practices; You are passionate about systems engineering building and evolving robust, secure, well-tested services and tools; You enjoy working in a small agile DevOps team building, deploying, automating and operating practical solutions in close collaboration with users. Desired technical skills: Professional experience in one or more of the following would be an asset: Infrastructure automation/configuration (Puppet), big data services and tools (Hadoop, Spark, Jupyter Notebooks), front-end development (Javascript), back-end development (Python, Java, Shell scripting), container technologies (Kubernetes). Please note that CERN Staff members are not eligible to apply for a Fellowship. Additional Information CERN would very much like to benefit from your expertise, commitment and passion. In return, CERN will provide you with: An employment contract for between six months (minimum) up to a maximum of 36 months. A stipend ranging from 5,281 to 6,558 Swiss Francs per month (net of tax). Coverage by CERN’s comprehensive health scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund. Depending on your individual circumstances: an installation grant, family, child and infant allowances as well as travel expenses to and from Geneva. 2.5 days of paid leave per month. Your Life @CERN Find out more here: https://hr.web.cern.ch/life-cern This is how you can apply: You will need the following documents to complete your application: A CV. A scanned PDF of your most recent relevant qualification. We recommend to add two recent letters of recommendation, giving an overview of your academic and/or professional achievements. You can upload these letters at the time of application if you have them to hand. You will also be provided with a link as soon as you have submitted your application to forward to your referees to upload their letters confidentially. Please note this must be done before the closing date. All applications should reach us no later than 29 September 2020. I'm interested Privacy Policy I'm interested Refer a friend Posted by Muriel COLSON share this job Powered by (Data Processor) Privacy Policy and Terms of Use Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share.
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