Scientific Data Engineer / Architect (m/f/d) in Dresden
Dresden
Dresden
Scientific Data Engineer / Architect (m/f/d) in Dresden
About us
Scionics Computer Innovation GmbH provides consulting, services, and support to academic institutions and scientific research organizations. We integrate information technology and data and image analysis techniques with biology and the life sciences.
Scionics is located in Dresden, Germany, and is part of the dynamic Biopolis Dresden research campus that includes the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) and its Center for Systems Biology Dresden (CSBD), the Center for Molecular and Cellular Bioengineering (CMCB) of the TU Dresden, and the Center for Theoretical Medicine (MTZ) which is part of the university hospital.
We work closely with all of these institutions and this provides our staff access to new technology and exciting projects and research in close contact with a highly international community of scientists who are world leaders in their respective fields. Scionics wishes to strengthen its expertise within its team providing onsite scientific computing services in the area of Research Data Management and Scientific Data Engineering.
Job Description
We seek to recruit a highly motivated individual to work as part of a scientific computing team at a client site that provides services in research data management, pipeline and workflow development, bioinformatics, bioimage analysis, and software development to the Dresden scientific community. This team is closely linked to academic research institutes, especially the MPI-CBG and associated CSBD, and with research groups working at the interface of biology, physics, and math. This provides an exciting and unique environment to work on multidisciplinary projects and access to a wide range of interesting data.
We seek to strengthen the team in the area of Research Data Management and Scientific Data Engineering and with the recruitment of a new Scientific Data Engineer / Architect.
Advances in sequencing, microscopy, and automation have created an environment in which vast amounts of data can be rapidly produced. Making this data available for analysis outside of the group in which it is produced for data-driven modelling and mathematical approaches requires that it is properly organized, structured, and associated with the appropriate metadata. The goal is to structure data appropriately to make it findable, accessible, interoperable, and reusable (FAIR).
The Scientific Data Engineer, working along with a team and directly with scientists, will help define and implement data management platforms and management infrastructure (image databases, metadata schemes, big-data workflow engines, data provenance infrastructure, etc.) as well as help research groups use these tools. In cooperation with research software engineers the scientific data engineer will help design and develop data pipelines and distributed computing workflows that enable access to large datasets for analysis and machine learning approaches.
A successful candidate will enjoy innovating and being creative in data design as well as in using existing tools and applications and testing and implementing new tools to efficiently solve data storage and metadata problems. In addition, the successful candidate will contribute to the teaching of scientists on the proper handling of data, metadata strategies and techniques, and will keep up-to-date with new trends in the field and emerging data management organizations and efforts such as the German National Scientific Data Infrastructure (NFDI).
Responsibilities Include
- Design and implement scalable data management systems for scientific data including digital microscopy, sequencing, and genomics data
- Help assemble and organize large datasets to make them available for data modelling and mathematical analysis approaches
- Collaborate with scientific researchers and facility leaders to assist in data related technical issues and to support their needs
- Work together with the team to support Good Scientific Practice (GSP) and making data Findable, Accessible, Interoperable, and Reusable (FAIR)
- Understand the basics of the GDPR and how it might apply to scientific data
- Assist institutions to improve their internal data handling processes and workflows
- Maintain awareness of, and integrate with, external efforts such as the NFDI
Essential Requirements
- Degree in Computer Science, IT, Mathematics, or related field or experience proving expertise. Master’s or PhD degree is a plus
- Proven experience in Research Data Management or as a Data Engineer or Data Steward with a minimum of three years of experience
- Experience in using data management tools, creating data pipelines, or optimizing data organization
- Hands-on experience managing and/or manipulating data programmatically with Python or and equivalent modern scripting or programming language
- Excellent communication skills and the ability to explain complex information in an easy-to-understand way
- Ability to multitask and to work in a multidisciplinary environment with rapidly changing projects
- Excellent command of English, both spoken and written
Desirable Experiences
- Experience with biological or scientific research data
- Experience with high performance computing and or large storage installations
- Open-source software development skills
Benefits
Contract: Scionics offers favorable contract conditions and salary based on experience. The position is intended to be a permanent position after an initial probation period of two years. Scionics is flexible in terms of remote and home office work.
Training Budget: Scionics provides a yearly budget for employee chosen self improvement, conferences or trainings.
Corporate culture: Scionics is an SME with strong ties to academia. If you work here, you will meet a lot of international people (~50% of your colleagues would be non-German) and get a good opportunity to broaden your horizons not only culturally but also with regard to modern science. The work environment in Scionics is informal and with less bureaucracy than a big corporation (but not as chaotic as a start-up).
Location: Scionics is headquartered in Dresden, a beautiful but still affordable city. The Scionics offices are located close to the river Elbe, with residential areas within walking distance.
Company stability: Scionics is a privately held, profitable company.
Contact Us
If you are interested in this position, please send your CV, cover letter and any other relevant documents to: dataengineer@scionics.com with the subject “Data Engineer”. Please also include contact information for a few references if possible.
Indem Sie bei uns arbeiten, werden Sie sowohl Ihre Erfahrungen und Kenntnisse einsetzen und teilen können als auch umfangreiches, neues Wissen hinzugewinnen.
Unser Arbeitsumfeld ist von einer spannenden Mischung aus unternehmerischer und wissenschaftlicher Kultur geprägt und bietet eine Vielzahl interessanter Aufgaben und Projekte, Zugang zu hochwertiger Hardware sowie flexible Arbeitszeiten.
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