Staff Engineer (Real Time Data Processing)

About the Role

We are looking for a Staff EngineerReal-time Data Processing to design and develop highly scalable, low-latency data streaming platforms and processing engines. This role is ideal for engineers who enjoy building core systems and infrastructure that enable mission-critical analytics at scale. Youll work on solving some of the toughest data engineering challenges in healthcare.

A Day in the Life

• Architect, build, and maintain a large-scale real-time data processing platform.
• Collaborate with data scientists, product managers, and engineering teams to define system architecture and design.
• Optimize systems for scalability, reliability, and low-latency performance.
• Implement robust monitoring, alerting, and failover mechanisms to ensure high availability.
• Evaluate and integrate open-source and third-party streaming frameworks.
• Contribute to the overall engineering strategy and promote best practices for stream and event processing.
• Mentor junior engineers and lead technical initiatives.

What You Need

• 8+ years of experience in backend or data engineering roles, with a strong focus on building real-time systems or platforms.
• Hands-on experience with stream processing frameworks like Apache Flink, Apache Kafka Streams, or Apache Spark Streaming.
• Proficiency in Java, Scala, or Python or Go for building high-performance services.
• Strong understanding of distributed systems, event-driven architecture, and microservices.
• Experience with Kafka, Pulsar, or other distributed messaging systems.
• Working knowledge of containerization tools like Docker and orchestration tools like Kubernetes.
• Proficiency in observability tools such as Prometheus, Grafana, OpenTelemetry.
• Experience with cloud-native architectures and services (AWS, GCP, or Azure).
• Bachelor's or Masters degree in Computer Science, Engineering, or a related field.