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# Scientific Data Engineer

- **Company:** R&D Partners
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Information Engineering, Data Infrastructure, Data Mining, Github, Python (Programming Language), Software Tools, Software Project Management, SQL Databases, Data Analytics, Tools for Reporting, Spotfire
- **Published:** September 27, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/scientific-data-engineer/48640433

## About the Role

engineering, and contributing to AI/ML, statistical, and modeling projects alongside data scientists and laboratory scientists. Ensure data quality and integrity throughout the data lifecycle by developing tools, maintaining documentation, and following software development best practices. Provide technical support and training for R&D software tools, helping users resolve issues, adopt new solutions, and maximize the value of data-driven technologies. Key Skills and Requirements Degree in Bioprocessing, Biochemical Engineering, or a related scientific field. Knowledge or experience in Data Science, Data Engineering, or data-intensive coding projects. Proficiency in SQL, specifically programming queries. Understanding of GitHub. Familiarity with Benchling (an Electronic Lab Notebook). Knowledge of Spotfire or Python is highly advantageous. For more information, please contact Jack Gordon. #J-18808-Ljbffr

## Description

Join a pioneering biotechnology company where your data engineering expertise will help drive innovation in gene therapy and improve the lives of patients with rare diseases. R&D Partners is seeking a Scientific Data Engineer to join an ambitious biotechnology company specializing in gene therapy and rare diseases. This role focuses on developing and maintaining R&D data infrastructure, supporting scientific workflows, and enabling data-driven decision-making across the organization. Please note that to be considered for this role you must have the right to work in this location. Responsibilities Develop and maintain R&D data infrastructure, including data models, pipelines, and electronic lab notebook (ELN) templates to support scientific workflows and data capture. Build SQL queries, dashboards, and reporting solutions to improve access to operational and scientific data across the R&D organization. Support data analysis activities by performing data mining, data exploration, feature


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