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Tier-1 brand, mid-level generalist data-platform role with broad skills and metro context increases competition.
Specialized data platform and streaming experience is moderately transferable but favors data-engineering backgrounds.
Explicit years plus mandatory distributed-systems, streaming, database, and language requirements make filters strict.
Design, develop, test, and maintain scalable backend services and data pipelines that operate across multiple data stores and streaming systems.
Own end-to-end feature delivery including design, implementation, testing, deployment, and production support focusing on scalability, reliability, and performance optimizations.
Drive performance improvements through indexing, query tuning, load testing, profiling, and instrumentation for observability in production environments.
Bachelor's degree with 4+ years related experience, or Master's degree with 2+ years, or PhD with 0 years relevant experience.
Strong backend engineering experience building production-grade services for large-scale distributed systems with emphasis on scalability, reliability, and performance.
Proficiency in Python and experience with another backend language such as Go, Java, or C++.
Experience with at least one relational or analytical database (schema design, query tuning, migrations) and streaming or queueing systems (e.g., Kafka, RabbitMQ).
Experienced in distributed system design, data pipelines, and backend service development at high scale.
Comfortable working with multiple database technologies including analytical/columnar stores and stream processing frameworks.
Demonstrates strong engineering discipline with hands-on experience in CI/CD, automated testing, production troubleshooting, and performance tuning.