Data Engineer

Job Summary:

•Design, develop, and maintain scalable data pipelines and architectures for the integration, transformation, and storage of large datasets.

•Optimize data flow and collection for cross-functional teams, ensuring efficient access and retrieval for business-critical analytics and applications.

•Implement, manage, and optimize data storage solutions in Snowflake.

•Integrate streaming data using Kafka to ensure real-time data availability and processing.

•Deploy and manage containerized data processing applications using Kubernetes in an Azure Cloud environment.

•Collaborate with data science and AI/ML teams to integrate and support Large Language Models (LLMs) and other advanced machine learning models.

•Work with healthcare data standards like HL7V2, HL7V3, and FHIR to ensure data interoperability across healthcare systems.

•Utilize Databricks for data engineering tasks, including data processing, analytics, and machine learning workflows.

•Write clean, scalable, and efficient code in Python and Java to support data engineering and software development initiatives.

•Collaborate with cross-functional teams to design and optimize data solutions that support AI-driven insights and healthcare applications.

Preferred Qualifications:

•Healthcare/Clinical data background.



Education: Bachelors Degree