Seargin is a dynamic multinational tech company operating in 50 countries. At Seargin, we drive innovation and create projects that shape the future and greatly enhance the quality of life. You will find our solutions in the space industry, supporting scientists in the development of cancer drugs, and implementing innovative technological solutions for industrial clients worldwide. These are just some of the areas in which we operate.
Data Engineer
Remote
European Union
Senior
B2B
Collaborate with solution and data architects to develop comprehensive data solutions, ensuring seamless integration and interoperability across clinical information systems.
Identify and implement appropriate data standards (such as HL7 v2/3, SMART-on-FHIR) and data models (such as OMOP, FHIR) that are suitable for both transactional and analytical use cases.
Develop systems for managing healthcare terminologies, mappings, and crosswalks, including their validation and testing processes.
Support the standardization of the Evidens Platform (EDC) by assessing, selecting, and implementing relevant data standards to enhance platform functionality and interoperability.
Employment based on a B2B contract
Opportunity to work in a stable, dynamically developing international company.
Chance to participate in interesting projects and work with the latest information technologies.
Attractive remuneration rates offered.
Involvement in the most prestigious international projects.
Access to Multisport benefits and private healthcare services.
Bachelor's or Master's degree in Computer Science, Data Science, Informatics, or a related field.
Hands-on experience with healthcare data, particularly within at least one of the following disease areas: oncology, neurology, immunology, infectious diseases, ophthalmology, cardiovascular, and metabolism.
Proficient in working with real-world data, specifically with the OMOP (Observational Medical Outcomes Partnership) Common Data Model.
Experience with integrating healthcare terminologies, including using tools such as OHDSI Athena and UMLS (Unified Medical Language System).
Proficiency in Python (with libraries like NumPy, pandas, etc.) or R. Strong knowledge and experience with SQL.
