Job Description:-

• 4+ years of experience in data engineering, with strong proficiency in Kafka and Python.
• Expertise in Kafka Streams, Kafka Connect, and Schema Registry for real-time data processing.
• Experience with Azure Databricks (or willingness to learn and adopt it quickly).
• Hands-on experience with cloud platforms (Azure preferred, AWS or GCP is a plus).
• Proficiency in SQL, NoSQL databases, and data modeling for big data processing.
• Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for data applications.
• Experience working with healthcare data (EHR, claims, HL7, FHIR, etc.) is a plus.
• Strong analytical skills, problem-solving mindset, and ability to lead complex data projects.
• Excellent communication and stakeholder management skills.

Key Responsibilities:

• Lead the design, development, and implementation of real-time data pipelines using Kafka, Python, and Azure Databricks.
• Architect scalable data streaming and processing solutions to support healthcare data workflows.
• Develop, optimize, and maintain ETL/ELT pipelines for structured and unstructured healthcare data.
• Ensure data integrity, security, and compliance with healthcare regulations (HIPAA, HITRUST, etc.).
• Collaborate with data engineers, analysts, and business stakeholders to understand requirements and translate them into technical solutions.
• Troubleshoot and optimize Kafka streaming applications, Python scripts, and Databricks workflows.
• Mentor junior engineers, conduct code reviews, and ensure best practices in data engineering.
• Stay updated with the latest cloud technologies, big data frameworks, and industry trends.