What are the responsibilities and job description for the Knowledge Engineer | Remote role | W2 Only | position at Xlysi?
Design and maintain enterprise knowledge repositories and document management solutions using SharePoint.
Work closely with business users, healthcare SMEs, data engineers, and architects to capture, organize, and govern organizational knowledge.
Develop and maintain metadata models, taxonomies, and information architecture standards.
Build and optimize data pipelines using Databricks and Snowflake to support reporting, analytics, and AI initiatives.
Transform healthcare data from multiple source systems into usable business knowledge assets.
Collaborate with data engineering teams to ensure data quality, lineage, governance, and accessibility.
Support enterprise search, knowledge discovery, and AI-powered information retrieval initiatives.
Create and maintain documentation, knowledge articles, process flows, and technical standards.
Work with structured and unstructured healthcare data, including clinical, operational, and financial datasets.
Participate in data governance activities and ensure compliance with healthcare regulations and organizational policies.
Partner with cross-functional teams to improve knowledge sharing and reduce information silos across the organization.
Required Skills & Experience
8 years of overall IT experience.
4 years of experience in Knowledge Management or Knowledge Engineering roles.
Strong hands-on experience with SharePoint Online and Microsoft 365 collaboration tools.
Experience working with Databricks, Apache Spark, and Lakehouse architectures.
Strong experience with Snowflake data warehousing and data modelling.
Solid understanding of Data Engineering concepts including ETL/ELT, data integration, and data quality management.
Experience working within healthcare environments and healthcare data domains.
Knowledge of healthcare standards such as HL7, FHIR, ICD, Claims, Provider, and Member data is highly desirable.
Strong SQL and data analysis skills.
Experience with Python, PySpark, or similar data engineering technologies.
Understanding of enterprise information architecture, metadata management, and taxonomy design
Work closely with business users, healthcare SMEs, data engineers, and architects to capture, organize, and govern organizational knowledge.
Develop and maintain metadata models, taxonomies, and information architecture standards.
Build and optimize data pipelines using Databricks and Snowflake to support reporting, analytics, and AI initiatives.
Transform healthcare data from multiple source systems into usable business knowledge assets.
Collaborate with data engineering teams to ensure data quality, lineage, governance, and accessibility.
Support enterprise search, knowledge discovery, and AI-powered information retrieval initiatives.
Create and maintain documentation, knowledge articles, process flows, and technical standards.
Work with structured and unstructured healthcare data, including clinical, operational, and financial datasets.
Participate in data governance activities and ensure compliance with healthcare regulations and organizational policies.
Partner with cross-functional teams to improve knowledge sharing and reduce information silos across the organization.
Required Skills & Experience
8 years of overall IT experience.
4 years of experience in Knowledge Management or Knowledge Engineering roles.
Strong hands-on experience with SharePoint Online and Microsoft 365 collaboration tools.
Experience working with Databricks, Apache Spark, and Lakehouse architectures.
Strong experience with Snowflake data warehousing and data modelling.
Solid understanding of Data Engineering concepts including ETL/ELT, data integration, and data quality management.
Experience working within healthcare environments and healthcare data domains.
Knowledge of healthcare standards such as HL7, FHIR, ICD, Claims, Provider, and Member data is highly desirable.
Strong SQL and data analysis skills.
Experience with Python, PySpark, or similar data engineering technologies.
Understanding of enterprise information architecture, metadata management, and taxonomy design