Staff Software Engineer- Backend

Design, develop, and maintain scalable, production-quality backend microservices and REST/gRPC APIs using your primary language and framework (e.g., Java/Spring Boot, Scala/Akka, Python/FastAPI/Django). Architect and support event-driven and real-time data solutions using messaging or streaming platforms such as Apache Kafka, Apache flink, Apache spark structured streaming, Pulsar, Pub/Sub, or similar. Collaborate in building and optimizing both streaming and batch data pipelines for reliable, timely data delivery. Integrate with, and optimize, relational (PostgreSQL, MySQL) or NoSQL databases, designing schema and high-performance queries. Leverage containerization (Docker) and orchestration (Kubernetes) to build and deploy cloud-native, resilient applications. Contribute to CI/CD pipelines, infrastructure as code, and cloud-native operational practices. Champion secure coding, observability, monitoring, and performance optimization across all services. Collaborate closely with product, data, DevOps, and engineering peers in Agile/Scrum cycles. Mentor team members, participate in code/design reviews, and foster knowledge sharing. Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience. Bachelor's degree or higher in Computer Science, Engineering, or a related technical discipline. 7+ years of hands-on software or data engineering experience, including designing and maintaining streaming or real-time data pipelines. Deep hands-on experience with distributed streaming platforms such as Kafka, Flink, Spark Structured Streaming, or Pulsar, and their associated tooling. Strong programming experience in Java, Scala, or Python for backend and distributed systems; proficiency in one major framework (Spring Boot, Django, FastAPI, Akka, etc.). In-depth understanding of event-driven architectures, stateful stream processing, windowing, and exactly-once delivery semantics. Experience architecting robust, high-performance systems optimized for latency, throughput, and resilience. Familiarity with cloud-based streaming services (AWS Kinesis, Google Pub/Sub, Azure Event Hubs) is a plus. Experience working with Docker and Kubernetes for containerization and orchestration is beneficial. Proven ability to lead architectural decisions, guide teams through complex technical challenges, and deliver scalable data solutions. Experience with real-time analytics, online feature stores, or ML pipelines in streaming environments. Experience with time-series or NoSQL databases commonly used in streaming data scenarios. Familiarity with CI/CD pipelines, infrastructure as code (IaC) practices, and DevOps tools. Active contributions to open source, or engagement in streaming/real-time data communities Subsidiary: