{"id":3674357,"url":"https://alion.io/job/nccr-automation-data-engineer-lab-digitalisation","title":"Data Engineer Lab Digitalisation","company":{"id":2497293,"name":"NCCR Automation","domain":"nccr-automation.ch","url":"https://alion.io/company/nccr-automation","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Refline","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"part_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Muttenz, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bioreactors","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"LIMS","optional":false},{"name":"Machine Learning","optional":false},{"name":"OPC UA","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-02T12:37:02Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-05T06:24:36Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Flexibility, self-determination, creativity, interdisciplinarity - our mission\nData Engineer Lab Digitalisation (50-80%)\nSchool of Life Sciences FHNW, Institute for Pharma Technology and Biotechnology\nYour tasks\nWe are digitalising our biotech laboratory: lab instruments, databases and analytics are to be brought together on one central data platform. You will play a key role in this.\nDesign and build a scalable data platform for laboratory and research data\nConnect lab instruments (e.g. anayltic instruments, spectrometers, bioreactors), existing databases and LIMS/ELN via interfaces and standards such as OPC UA. \nDevelop and operate automated data pipelines (ETL/ELT), including data quality, metadata management and versioning \nMake data available for analytics, dashboards and machine learning in line with the FAIR principles\nEnsure data security, access control and data integrity, and document and train users in close collaboration with research, lab and IT teams\nIn addition, you will be actively involved in applied research projects with several industrial partners\nYour profile\nYou combine solid software engineering with a passion for the life sciences.\nDegree (Bachelor/Master) in computer science, data science, bioinformatics or a comparable field \nSeveral years of data engineering experience with Python and SQL, workflow tools and containers (Docker)\nKnowledge of relational and NoSQL databases, cloud or on-premise data platforms and API development\nExperience with laboratory data, instrument integration, LIMS/ELN or regulated (GxP) environments is a plus\nIndependent, structured way of working, enjoyment of interdisciplinary collaboration, and good German and good English skills\nThe FHNW School of Life Sciences offers state-of-the-art technical, laboratory and office facilities. Contributing to the school’s highly motivating working environment - which is second to none - are its collaboration with a large number of companies and institutions in Switzerland and abroad, a widely varied programme of scientific events, and daily contact with young students in research and teaching. The FHNW is also committed to equal opportunities and the compatibility of private and professional life.\nWill you soon belong to our team? 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