Sr Semantic Software Engineer – Research Data and Analytics

Role Description:

Amgen Research’s Semantic Graph Team is seeking a dedicated and skilled Sr Software Engineer with semantic technologies experience to maintain, operate, and enhance the new Research Taxonomy Foundation. This role focuses on building reliable software services and data pipelines that support taxonomy, ontology, and controlled vocabulary management across research data platforms, using technologies such as Python, RDF, SPARQL, and cloud-based engineering tools.

The ideal candidate should bring strong software engineering fundamentals, experience designing and supporting production platforms, and practical knowledge of semantic technologies and data standards. Experience in the pharmaceutical or biotech industry is preferred, along with the ability to work across application development, data integration, and platform operations. A solid understanding of data architecture, CI/CD, and maintainable system design is essential for success in this role.

In this role, you will be responsible for ensuring the ongoing reliability, scalability, and evolution of the Research Controlled Vocabulary Foundation, including application support, data processing, semantic services, and integration with downstream research systems. The position combines software engineering delivery with semantic domain knowledge to enable high-quality taxonomy and controlled vocabulary services across the research ecosystem.

Roles & Responsibilities:

Maintain, operate, and enhance a Research Controlled Vocabulary Foundation as a production software platform.

Develop and support software services, APIs, and data pipelines using Python and related technologies to power taxonomy and controlled vocabulary workflows.

Implement and maintain semantic capabilities using RDF, SPARQL, and linked data approaches where appropriate.

Ensure platform reliability, performance, monitoring, and operational support for taxonomy management services.

Design and maintain integrations between the Research Controlled Vocabulary and upstream or downstream research systems, including relational and graph-based data sources.

Implement and optimize CI/CD pipelines and engineering best practices using GitLab and cloud platforms such as AWS.

Collaborate with product owners, data architects, scientists, and business stakeholders to deliver scalable software solutions that meet research needs.

Contribute to technical design, estimation, sprint planning, testing, and release activities for platform enhancements.

Maintain documentation for platform architecture, support processes, data flows, and operational procedures.

Apply semantic modeling knowledge to support taxonomy, ontology, and controlled vocabulary management in alignment with research data standards, and partner with the enterprise ontology/controlled vocabulary platform team to support transition activities from the current internal Research Taxonomy Foundation to the future COTS platform, including reconciliation, data migration, and related integration efforts.

Basic Qualifications and Experience:

Master's or Bachelor's degree with 8 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field

Preferred Qualifications and Experience:

3+ years of experience in implementing and supporting biopharma scientific research data analytics (software platforms)

Functional Skills:

Must-Have Skills:

Advanced Semantic and Relational Data Skills: Proficiency in Python, RDF, SPARQL, Graph Databases (e.g. Allegrograph), SQL, relational databases, ETL pipelines, big data technologies (e.g. Databricks), semantic data standards (OWL, W3C, FAIR principles), ontology development and semantic modeling practices.

Cloud and Automation Expertise: Strong experience in using cloud platforms (preferably AWS) for data engineering, along with Python for automation, data federation techniques, and model-driven architecture for scalable solutions.

Technical Problem-Solving: Excellent problem-solving skills with hands-on experience in test automation frameworks (pytest), scripting tasks, and handling large, complex datasets.

Good-to-Have Skills:

Experience in biotech/drug discovery data engineering

Experience applying knowledge graphs, taxonomy and ontology concepts in life sciences and chemistry domains

Experience with graph databases (Allegrograph, Neo4j, GraphDB, Amazon Neptune)

Familiarity with Cypher, GraphQL, or other graph query languages

Experience with big data tools (e.g. Databricks)

Experience in biomedical or life sciences research data management

Soft Skills:

Excellent critical-thinking and problem-solving skills

Strong communication and collaboration skills

Demonstrated awareness of how to function in a team setting

Demonstrated presentation skills

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.