{"id":24001,"date":"2026-08-03T10:38:25","date_gmt":"2026-08-03T08:38:25","guid":{"rendered":"https:\/\/dhd-blog.org\/?p=24001"},"modified":"2026-08-03T10:38:25","modified_gmt":"2026-08-03T08:38:25","slug":"universitaet-heidelberg-research-data-engineer-100-e13-w-m-d","status":"publish","type":"post","link":"https:\/\/dhd-blog.org\/?p=24001","title":{"rendered":"Universit\u00e4t Heidelberg: Research Data Engineer 100% E13 (w\/m\/d)"},"content":{"rendered":"\n<p>Heidelberg University is a comprehensive university with a strong focus on research and international standards. With around 32,200 students and 9,540 employees, including numerous top researchers, it is a globally respected institution that also has outstanding economic significance for the Rhine-Neckar metropolitan region.<\/p>\n<p>The Heidelberg Center for Digital Humanities is one of Germany\u2032s leading institutions in the fields of digital and computational humanities. Its key areas of focus are digital linguistics, digital heritage, and AI\/machine learning. Thanks to its close ties with the Interdisciplinary Center for Scientific Computing (IWR), the HCDH pursues the computational humanities with particular intensity.<\/p>\n<p>The Research Data Engineer full-time position (E13, 100%) for a term of 4 years, with the option to extend is available at the Heidelberg Center for Digital Humanities (HCDH) starting December 1, 2026 (or earliest possible).<\/p>\n<p><b>Your responsibilities:<\/b><\/p>\n<ul>\n<li>Bridging the gap between <b>cultural heritage data<\/b> and <b>advanced computational research<\/b>: Design and build data storage layers and data processing pipelines that enable our humanities researchers to create and analyze massive, heterogeneous datasets (including legacy data)\u2014ranging from historical texts and archives to multimedia, 3D and spatial data<\/li>\n<li><b>Research Collaboration:<\/b> Act as the technical consultant for humanities scholars, translating complex research questions into viable computational and database requirements<\/li>\n<li><b>Data Pipelines:<\/b> Design, implement, and maintain scalable pipelines to ingest, clean, and harmonize diverse cultural heritage and other data and create interoperable datasets for research<\/li>\n<li><b>Data architecture:<\/b> Design, implement, and maintain data structures and connect to existing data storage layers and infrastructure<\/li>\n<li><b>Semantic Web &amp; Knowledge Graphs:<\/b> Develop and optimize graph databases, ontologies, and semantic models (e.g., using RDF, OWL, CIDOC-CRM) to interconnect complex historical and cultural data<\/li>\n<li><b>Tool Development &amp; Automation:<\/b> Build custom APIs, and scripts (primarily in Python) to automate data ingestion, text-mining, and natural language processing (NLP) workflows<\/li>\n<li><b>FAIR and FAIR4RS principles:<\/b> Collaborate with the Research Data Unit and Scientific Software Center and its Data Science Unit at the IWR, and the University Computing Centre (HPC and storage infrastructure)<\/li>\n<\/ul>\n\n\n\n<p><b>Your profile: <\/b><\/p>\n<ul>\n<li><b>Education &amp; Background:<\/b> Preferably a PhD, but MA\/MSc are encouraged to apply<\/li>\n<li><b>Soft Skills:<\/b> Strong communication skills to effectively collaborate across interdisciplinary teams of software engineers and traditional humanities scholars<\/li>\n<li><b>Core Tech Stack:<\/b> Excellent knowledge of <b>Python<\/b> (plus libraries like Open3D, Pandas, SpaCy, or NLTK) and version control using Git, experience with Rust and\/or PyTorch is a plus<\/li>\n<li><b>Database &amp; Semantic Web Skills:<\/b> Strong experience with databases (e.g., Neo4j, GraphDB, NoSQL, SQL) and semantic web technologies (e.g., SPARQL, JSON-LD)<\/li>\n<li><b>DH Standards:<\/b> Ideally knowledge of text encoding standards (e.g., <b>TEI-XML<\/b>) and metadata schemas (e.g., Dublin Core, MODS, LIDO); desirable: Experience with working with humanities\u2019 data<\/li>\n<li>Independent and structured <b>work style<\/b>, ability to work in teams and to <b>fixed timelines<\/b><\/li>\n<li><b>Language requirements:<\/b> Very good English language skills, desirable: basic German skills<\/li>\n<\/ul>\n<p><b>We offer: <\/b><\/p>\n<ul>\n<li>The opportunity to work at the cutting edge of digital and computational humanities using modern AI and data engineering methods<\/li>\n<li>Work in an innovative environment with the opportunity of professional training and qualification in the emerging professional field of research data engineering<\/li>\n<li>A highly collaborative, interdisciplinary, and international research environment<\/li>\n<li>Support for active contributions to the Open Source and Digital Humanities communities<\/li>\n<li>Excellent opportunities for independent research and further academic training<\/li>\n<li>Flexible working hours and a good work-life balance; part-time remote work is possible<\/li>\n<li>Opportunity for further training and building a professional network by participating in national and international conferences<\/li>\n<li>A dedicated team that supports each other<\/li>\n<li>Workplace in the very Center of Heidelberg Altstadt with good public transport<\/li>\n<li>Access to university sports offers<\/li>\n<li>Support for employee mobility through a subsidized Deutschlandticket<\/li>\n<\/ul>\n<p>The position is a 4-year fixed-term position with the possibility of extension. Remuneration is based on the TV-L collective agreement (pay group 13). The position is suitable for job-sharing.<\/p>\n<p>We look forward to receiving your application (in English), including the following documents: cover letter, CV including a project list, proof of academic degree, employment references and list of references (2-3 names and contact details), by <b>14 September 2026<\/b>, sent to as <b>a single PDF file<\/b> via email to <a href=\"mailto:nele.schneidereit@uni-heidelberg.de\">nele.schneidereit@uni-heidelberg.de<\/a> (max. of 25 MB).<\/p>\n<p>There will be a two-stage process, with online interviews taking place in the first half of October. We will invite the remaining candidates to an <b>in-person interview on October 23<\/b>. Please save the date.<\/p>\n<p>Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply. People with severe disabilities will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available at <a href=\"https:\/\/www.uni-heidelberg.de\/en\/job-market\" target=\"_blank\" rel=\"noopener\">www.uni-heidelberg.de\/en\/job-market<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Heidelberg University is a comprehensive university with a strong focus on research and international standards. With around 32,200 students and 9,540 employees, including numerous top researchers, it is a globally respected institution that also has outstanding economic significance for the Rhine-Neckar metropolitan region. The Heidelberg Center for Digital Humanities is one of Germany\u2032s leading institutions [&hellip;]<\/p>\n","protected":false},"author":468,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[528,535,1986,273,601,97,1172,206,136,1985,282],"class_list":["post-24001","post","type-post","status-publish","format-standard","hentry","category-stellen","tag-collaboration","tag-computational-humanities","tag-data-architecture","tag-digital-cultural-heritage","tag-digital-heritage","tag-forschungsdaten","tag-knowledge-graph","tag-python","tag-stellenausschreibung","tag-tool-development","tag-universitaet-heidelberg"],"_links":{"self":[{"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/posts\/24001","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/users\/468"}],"replies":[{"embeddable":true,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=24001"}],"version-history":[{"count":1,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/posts\/24001\/revisions"}],"predecessor-version":[{"id":24002,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=\/wp\/v2\/posts\/24001\/revisions\/24002"}],"wp:attachment":[{"href":"https:\/\/dhd-blog.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=24001"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=24001"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dhd-blog.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=24001"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}