Overview
Role Overview
We are seeking a Senior Software Engineer (SSE) with strong expertise in Kafka, Python, and Azure Databricks to lead and contribute to our healthcare data engineering initiatives. This role is pivotal in building scalable, real-time data pipelines and processing large-scale healthcare datasets in a secure and compliant cloud environment.
The ideal candidate will have a solid background in real-time streaming, big data processing, and cloud platforms, along with strong leadership and stakeholder engagement capabilities.
Key Responsibilities
We are seeking a Senior Software Engineer (SSE) with strong expertise in Kafka, Python, and Azure Databricks to lead and contribute to our healthcare data engineering initiatives. This role is pivotal in building scalable, real-time data pipelines and processing large-scale healthcare datasets in a secure and compliant cloud environment.
The ideal candidate will have a solid background in real-time streaming, big data processing, and cloud platforms, along with strong leadership and stakeholder engagement capabilities.
Key Responsibilities
- Design and develop scalable real-time data streaming solutions using Apache Kafka and Python.
- Architect and implement ETL/ELT pipelines using Azure Databricks for both structured and unstructured healthcare data.
- Optimize and maintain Kafka applications, Python scripts, and Databricks workflows to ensure performance and reliability.
- Ensure data integrity, security, and compliance with healthcare standards such as HIPAA and HITRUST.
- Collaborate with data scientists, analysts, and business stakeholders to gather requirements and translate them into robust data solutions.
- Mentor junior engineers, perform code reviews, and promote engineering best practices.
- Stay current with evolving technologies in cloud, big data, and healthcare data standards.
- Contribute to the development of CI/CD pipelines and containerized environments (Docker, Kubernetes).
- 4+ years of hands-on experience in data engineering roles.
- Strong proficiency in Kafka (including Kafka Streams, Kafka Connect, Schema Registry).
- Proficient in Python for data processing and automation.
- Experience with Azure Databricks (or readiness to ramp up quickly).
- Solid understanding of cloud platforms, with a preference for Azure (AWS/GCP is a plus).
- Strong knowledge of SQL and NoSQL databases; data modeling for large-scale systems.
- Familiarity with containerization tools like Docker and orchestration using Kubernetes.
- Exposure to CI/CD pipelines for data applications.
- Prior experience with healthcare datasets (EHR, HL7, FHIR, claims data) is highly desirable.
- Excellent problem-solving abilities and a proactive mindset.
- Strong communication and interpersonal skills to work in cross-functional teams.
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