Software Engineer – Data Discovery

We are looking for a dynamic Software Engineer to join the EBI Search project [PMID: 40322924], a scalable text search engine providing easy and uniform access to the biological data resources hosted at the European Bioinformatics Institute (EMBL-EBI).

EBI Search provides the central discovery infrastructure indexing more than 6 billion data objects across EMBL-EBI and external resources. It enables search and cross-linking across more than 100 biological data domains via web interfaces and RESTful APIs. You will join a team of software developers working together to support scientific research and FAIR data access across multiple disciplines.

Your role

In this exciting role you will contribute to:

• Integration and indexing of biological data and metadata, and provision of these through user-friendly web interfaces and web services for the international research community;
• Development of new features within an established and evolving codebase;
• Integration of the search platform with emerging AI technologies to enhance data discovery and improve user experience;
• Development of lightweight and efficient approaches for integrating data from multiple domains;
• Collaboration with colleagues across EMBL-EBI, applying industry-standard best practices to create and maintain efficient, reusable and well-documented software.

You have

• A degree in Computer Science or a related field;
• A minimum of two years’ experience in software development;
• Good knowledge of Java;
• Experience with JavaScript and/or TypeScript;
• Experience with scripting languages such as Python and Bash;
• Good communication skills;
• Familiarity with modern software development practices and tools, including version control systems, CI/CD pipelines and automated testing.

You may also have

• Experience in biomolecular or biomedical data and metadata integration;
• Working knowledge of Solr, Lucene or Lucene-based search technologies;
• Knowledge of Docker, Kubernetes or other deployment technologies;
• Knowledge of additional data storage technologies, including relational databases, graph databases and NoSQL systems;
• Familiarity with Linux/Unix environments;
• Experience with collaborative development tools such as Jira and Confluence;
• Experience with machine learning approaches, ideally in the context of data discovery.