Kontakt.io

Data Engineer

• Lead the team in designing and building scalable data pipelines (batch & streaming) to process RTLS, IoT, and EHR data.
• Implement real-time event processing architectures using Kafka.
• Optimize ETL/ELT processes for efficient data ingestion, transformation, and storage.
• Develop and maintain data lakes and warehouses for analytics and machine learning applications.
• Create scalable data layers—bronze, silver, and gold—that facilitate advanced analytics and machine learning applications.
• Partner with software engineers and cloud teams to maintain a highly available data platform.
• Work closely with third-party vendors (e.g., EPIC, Cerner, Meditech) to integrate, standardize, and secure data from EHRs.
• Initiate and participate in architectural decisions to improve scalability, resiliency, and system efficiency.
• Ensure HIPAA and healthcare compliance standards are met in data storage and transmission.
• Optimize query performance, indexing, and partitioning for large-scale data processing.
• Implement role-based access control (RBAC), encryption, and anonymization for sensitive healthcare data.

Data Platform Lead

Engineer

• Integrating Kontakt.io with hospital systems such as EHR/EMR, ADT, nurse call, staffing, and operational platforms
• Supporting and validating integrations using APIs, HL7, FHIR, or other healthcare data exchange methods
• Mapping real clinical workflows to system data flows and configurations
• Partnering closely with Deployment Project Managers during implementation
• Supporting deployment planning, integration testing, go-live, and stabilization
• Participating in onsite or remote customer sessions as needed
• Acting as a technical bridge between hospital IT, clinical stakeholders, and internal teams
• Explaining integration behavior, limitations, and tradeoffs clearly and honestly
• Helping customers understand how to operationalize integrations effectively
• Diagnosing and resolving integration issues in production environments
• Supporting post-deployment optimization and expansion use cases
• Documenting integration patterns, risks, and best practices for scale
• Providing grounded feedback to Product and Engineering based on field reality
• Helping shape integration standards, tooling, and deployment playbooks
• Improving repeatability and reducing deployment risk over time

Data Platform Lead

Integration Clinical Engineer