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Working Student, Data & Analytics (m/f/d)

KNIME AG · Berlin

Publicada em 02/09/2026

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MissionSupport the Data & Analytics team in its day-to-day work, from pipelines to Data Apps and Reports to answering business questions.Role OverviewAs a Working Student in the Data & Analytics team, you will work alongside our analysts on what the week actually needs: a pipeline that has to keep running, a Data App a team is waiting for, a question someone needs answered. You will work in Knime every day, on things people across the company use. This is a role with real ownership: you get clearly scoped tasks and regular check-ins, and between them you work independently.ResponsibilitiesSupport the team day to day: take on the analysis, Report, or fix the week calls for, and see it throughBuild and maintain data ingestion workflows, and keep scheduled pipelines running as our data sources changeBuild Data Apps and Reports that teams across Knime use to answer their own questionsResearch questions other teams bring us, and come back with an answer they can act onImprove existing workflows, Data Apps, and Reports: performance, cleanup, and documentationOwn your tasks end to end: ask the scoping questions up front, execute independently, and hand over results clearlyRequirementsEnrolled at a university or Hochschule in Berlin, based in Berlin, with at least 12 months of study remainingAvailable at least 16 hours a week, and on site in our Kreuzberg office two days a weekWorking knowledge of Knime and data science fundamentalsSolid SQL and database basicsYou research on your own: you find the sources, judge what is relevant, and come back with an answer instead of a list of linksYou draft Data Apps and Reports with AI support, and can explain the resultA high degree of independence: you structure your own work and unblock yourself with documentation and research, and you know when to askCare and reliability when working on things other people depend onFluent in EnglishHow to Stand outA Knime L3 certificationExperience with schedules, spaces, and deployments in
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