Knowledge Engineer
Data Interoperability / Python / Java / Frontend Programming / FHIR, HL7v2, SNOMED or LOINC / Stakeholder Management / English
Project:
We are seeking a Knowledge Engineer to work with our customer, a big pharmaceutical company in Basel.
Background:
Our goal is to activate data and build products within Roche Information Solutions (RIS). We develop data technologies, algorithms, models, and analytics to enable continuous discovery and assess economic value for the RIS portfolio. This involves building reusable data products for Diagnostics and establishing data architecture to link data products across Diagnostics and beyond. We also strengthen data skills and mindsets and provide Real World Data and information science expertise to Diagnostics and data & analytics across Roche.
The Knowledge Engineer will be part of the RIS Data and Analytics team and contribute to creating a highly efficient environment for driving semantic data interoperability for digital solutions in RIS. The role will also significantly contribute to elevating data sources to the next level of quality by ensuring their physical, conceptual, and semantic coherence, integrity, and adherence to standards. With that, the role will contribute fundamentally to making data FAIR for Diagnostics.
Key Responsibilities:
1. Collaborate with various product teams to shape the development and integration of data models and standardization into the RIS product portfolio and enable FAIR data services.
2. Collaborate with engineering and business teams and co-drive projects to implement interoperability standards for Roche devices and digital products adhering to FAIR principles.
3. Investigate innovative methods to generate new business insights from interlinked data sources (lab and clinical) that may mature into new features of RIS digital products.
4. Drive the adoption and integration of interoperability standards including terminological resources (e.g., FHIR, HL7v2, LOINC, SNOMED) for RIS digital products.
5. Engage with internal key customers and stakeholders to understand their business needs, pain points using a customer-centric approach.
6. Co-create robust solutions starting out from prototypes and MVPs.
7. Drive automation of data and software services to achieve continuous delivery e.g., by setting up code repositories, automation pipelines, quality assurance, etc.
Requirements:
1. Minimum 3 years of experience working with data interoperability.
2. University Degree in Computer Science / Engineering related fields, preferably PhD degree (such as Software Engineering, Architecture, Data Science, Mathematics, Bioinformatics, or similar areas of academic discipline).
3. Strong software engineering skills and various programming languages such as Python, Java. Any knowledge of frontend programming languages such as Typescript, Angular, etc. is a plus. Any knowledge of data engineering and cloud skills is a plus.
4. Background in data interoperability technologies, such as data integration, data standards, and terminologies (e.g., FHIR, HL7v2, SNOMED, or LOINC).
5. Good knowledge in (meta) data management approaches such as relational and graph databases.
6. Strong stakeholder management and collaboration skills.
7. Ability to work independently in cross-functional and distributed teams.
8. Ability to work in changing, agile, multinational, and multiple location environments.
9. Very good communication and presentation skills.
10. Fluency in English.
Preferred Qualifications:
Experience in the pharmaceutical / medical device environment and in diagnostics is a plus.
Work Arrangement:
This is a hybrid work model - at least 1 day per week onsite.