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Tier-1 brand, mid-level generalist title, metro location, and broad skillset increase applicant competition.
Core data engineering and distributed-systems skills transfer well across industries.
Explicit years plus mandatory distributed-systems, streaming, database, and language requirements make shortlisting strict.
Design, implement, test, and maintain backend services and high-scale data pipelines across distributed data stores and streaming systems.
Own end-to-end feature development including schema changes, data transformations, query and write performance optimization, and production support.
Drive system scalability, reliability, performance, and observability improvements through profiling, benchmarking, instrumentation, and troubleshooting.
Bachelor's degree with 4+ years experience OR Master's degree with 2+ years OR PhD with 0 years experience in software engineering.
Strong backend engineering experience with production-grade services and distributed systems focusing on scalability, reliability, and performance.
Hands-on experience with at least one relational or analytical database including schema design and query tuning; and experience with streaming or queueing systems (e.g., Kafka, RabbitMQ).
Proficiency in Python and at least one other backend language such as Go, Java, or C++; strong fundamentals in system design, data structures, algorithms, concurrency, and modern software engineering practices including CI/CD and automated testing.
Experienced backend engineer with strong focus on large-scale distributed data systems and streaming pipelines.
Skilled in performance tuning, troubleshooting production issues, and improving data infrastructure efficiency and observability.
Comfortable leading features end-to-end including design, implementation, deployment, and production support in a collaborative, iterative environment.