Responsibilities: Develop and maintain critical backend services and APIs, primarily using Python (e.g., Flask, FastAPI). Support, maintain, and contribute to existing Java-based services and libraries (e.g., Spring Boot), demonstrating polyglot flexibility. Architect cloud-native solutions that are built to run on Google Cloud Platform (GCP), leveraging GKE, Pub/Sub, and BigQuery. Design and optimize data-intensive applications that interface with large-scale data stores, including BigQuery. Lead technical design discussions, write detailed design documents, and mentor junior engineers on the team. Drive continuous improvements in system architecture, reliability, performance, and CI/CD processes. Own services end-to-end, including monitoring (DataDog, etc.), setting SLOs, and participating in on-call rotations. Requirements: 5+ years of professional backend engineering experience. Expert-level proficiency in Python for backend development and data-intensive applications. Professional experience with Java (e.g., Spring Boot) and a willingness to work in a polyglot environment. Proven, deep hands-on experience designing and operating solutions on Google Cloud Platform (GCP), with production expertise in Google Kubernetes Engine (GKE), BigQuery, and Pub/Sub. Experience with event-driven architectures, DDD, and TDD. Experience with big data technologies (Spark, Kafka) and integrating ML models is a strong plus. Experience with large-scale data stores, including relational databases and data warehouses like BigQuery. A strong sense of ownership and a drive for technical excellence. Experience leveraging modern IDEs and AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate development cycles.