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Tier-1 employer and mid-career technical role increase candidate competition.
Deep data-platform, streaming, and multi-tenant expertise required, limiting cross-industry transferability.
Explicit 7+ years and strong mandatory platform and tech requirements imply high filtering rigor.
Own end-to-end data plane infrastructure including relational, analytical/columnar, object storage, caching stores, streaming, compute pipelines, and performance tooling at production scale.
Drive platform performance aspects such as query/write latency, indexing/sharding, capacity planning, cost-efficiency, multi-tenant isolation, and data operations including backup, restore, and migrations.
Collaborate with product engineering teams to evolve platform architecture, ensure data correctness, reliability, and scalability via design reviews, code reviews, and mentorship.
Bachelor's with 7+ years or Master's with 4+ years or PhD with 1+ year in Computer Science, Software Engineering, or related.
Strong backend engineering experience building and operating scalable, reliable production-grade data-intensive services.
Proven experience with large-scale distributed systems and operating/tuning OLTP (e.g., PostgreSQL) and analytical databases (e.g., ClickHouse).
Experience with streaming/queueing systems (e.g., Kafka), proficiency in Python plus at least one other backend language (Go, Java, C++), and performance engineering including profiling and benchmarking.
Technical leader experienced in cloud-native and containerized environments (Kubernetes, AWS/GCP) with strong distributed systems design skills.
Practitioner with in-depth knowledge of data platform capacity modeling, multi-tenant isolation, cost control, and observability instrumentation development.
Experienced in end-to-end ownership of scalable data pipelines, performance tooling, data reliability operations, and mentoring/technical leadership within cross-team environments.