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 Master’s degree in Computer Science, Engineering, or a related field.