Direct message the job poster from heydonto ai api
heydonto is seeking a talented data engineer to join our team and play a vital role in the development of the heydonto data mapper and the integration of knowledge graphs (kgs) with large language models (llms). This position involves working on cutting-edge technologies to standardize and process data from various electronic health record (ehr) systems, enhance data interoperability, and provide contextual insights for personalized medicine.
key responsibilities
* data standardization and transformation:
* convert diverse data structures from various ehr systems into a unified format based on fhir standards.
* map and normalize incoming data to the fhir data model, ensuring consistency and completeness.
* kafka integration:
* consume and process events from the kafka stream, produced by the data writer module.
* deserialize and validate incoming data to ensure adherence to required standards.
* separate data streams for warehousing and ai model training, applying specific preprocessing steps for each purpose.
* prepare and validate data for storage and machine learning model training.
* error handling and loggin:
* implement robust error handling mechanisms to track and resolve data mapping issues.
* maintain detailed logs for auditing and troubleshooting purposes.
knowledge graphs and llm integration:
* data ingestion and processing:
* use llms to extract structured data from ehrs, research articles, and clinical notes.
* ensure semantic consistency and interoperability during data ingestion.
* knowledge graph construction:
* integrate extracted data into a knowledge graph, representing entities and relationships for semantic data integration.
* implement contextual understanding and querying of complex relationships within the kg.
* advanced predictive modeling:
* leverage kgs and llms to enhance data interoperability and predictive analytics.
* develop frameworks for contextualized insights and personalized medicine recommendations.
* feedback loop:
* continuously update the knowledge graph with new data using llms, ensuring up-to-date and relevant insights.
collaboration and communication
* work closely with cross-functional teams
* collaborate with data scientists, ai specialists, and software engineers to design and implement data processing solutions.
* communicate effectively with stakeholders to align on goals and deliverables.
* contribute to engineering culture:
* foster a culture of innovation, collaboration, and continuous improvement within the engineering team.
qualifications
experience
* proven experience as a data engineer or similar role:
* strong background in data processing, standardization, and integration, particularly in healthcare domains.
* experience with fhir standards:
* familiarity with implementing fhir-compliant data models and mapping diverse data structures to fhir resources.
* expertise in kafka and streaming data:
* experience with kafka or similar streaming platforms for real-time data processing and integration.
* knowledge graph and llm experience:
* experience working with knowledge graphs and large language models, particularly in healthcare data contexts.
skills
* strong problem-solving skills:
* ability to design innovative solutions for complex data integration and processing challenges.
* proficiency in programming languages:
* strong skills in python or other relevant programming languages for data engineering.
* database and querying skills:
* proficiency in sql and experience with both relational and nosql databases.
* ability to articulate complex technical concepts and collaborate effectively with various stakeholders.
technical expertise
* python: proficient in python programming, with experience in data processing and integration.
* fhir and hl7: familiarity with healthcare standards like fhir and hl7 for data interoperability.
* kafka: experience with kafka for streaming data integration and processing.
* knowledge graphs: experience with graph databases like neo4j or rdf-based systems.
* machine learning: familiarity with machine learning models and ai frameworks.
* docker and kubernetes: experience with containerization and orchestration tools is a plus.
* work type: on-site
* salary offer: negotiable
* english level: native or advanced
if you are interested in applying, please send your cv in english to maria@heydonto.com, mentioning the name of the position you are applying for in the subject of the email. In the body of the email, please include the following information:
* salary expectations
* availability for interview
* availability to join the team
seniority level
* seniority level
mid-senior level
employment type
* employment type
full-time
job function
* job function
information technology
* industries
software development
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