4 days ago
Responsibilities
- Own and evolve relational, analytical/columnar, object-storage, and caching data stores, including schema design, migrations, retention, indexing, and sharding.
- Design and operate streaming and queueing systems that move data from ingestion to queryable form.
- Build and scale stream processors, writers, schedulers, distributed worker fleets, and other data-processing pipelines.
- Own data-plane performance, including latency, throughput, query and write optimization, capacity modeling, quotas, rate limits, cost attribution, and tenant isolation.
- Build load-testing, profiling, benchmarking, observability, and telemetry tooling for production-scale systems.
- Manage backup and restore, retention and deletion, replication, migration and backfill, and data-quality operations.
- Develop, test, maintain, debug, and support production services and internal tools in Python and/or Go.
- Contribute to architecture, monitoring, on-call support, root-cause analysis, design reviews, code reviews, documentation, and engineer mentorship.
Requirements
- Bachelor’s degree with 7+ years of related experience, or a master’s degree with 4+ years, or a PhD with 1+ year, in computer science, software engineering, or a related field.
- Strong backend software engineering experience building and operating scalable, reliable, production-grade data-intensive services and platforms.
- Experience designing and troubleshooting large-scale distributed systems across scalability, availability, performance, reliability, and fault tolerance.
- Hands-on experience operating and tuning an OLTP database and an analytical, columnar, or time-series store, including schema design, indexing, query tuning, and migration safety.
- Production experience with streaming or queueing systems, including partitioning, consumer groups, delivery guarantees, backlog handling, and dead-letter handling.
- Experience scaling data-processing compute through concurrency tuning, batching, backpressure, and sustained-load throughput optimization.
- Strong Python proficiency and solid experience with at least one additional backend language such as Go, Java, or C++.
- Demonstrated performance engineering experience with profiling, benchmarking, and load testing.
- Experience with Kubernetes, containerized environments, and public cloud platforms such as AWS or GCP.
- Ability to independently design, develop, debug, test, and maintain software with minimal guidance.
- Preferred qualifications include operating ClickHouse or comparable stores at scale, capacity modeling or FinOps, multi-tenant isolation, disaster recovery, OpenTelemetry pipelines, Pyroscope or py-spy, distributed task frameworks, stream processing, distributed query engines, model-serving infrastructure, cloud/SaaS and air-gapped deployments, technical leadership, mentoring, and cross-team communication.
Tech Stack
Apache FlinkApache KafkaAWSC++ClickHouseGoGoogle BigQueryGoogle Cloud PlatformJavaKubernetesMySQLPostgreSQLPrestoPythonRabbitMQSnowflake
Categories
BackendData Engineering
About Cisco
Cisco is the worldwide technology leader that is revolutionizing the way organizations connect and protect in the AI era. For more than 40 years, Cisco has securely connected the world. With its industry leading AI-powered solutions and services, Cisco enables its customers, partners and communities to unlock innovation, enhance productivity and strengthen digital resilience. With purpose at its core, Cisco remains committed to creating a more connected and inclusive future for all.