Staff Software Engineer - Data & Scalability Platform (hybrid)

Cisco•San Francisco, CA

7d•$186,900 - $267,700•Hybrid

About The Position

The Staff Software Engineer on the Data & Scalability Platform team will provide technical leadership for the architecture, scalability, and cost of the data plane, including data stores, streaming and compute components, and tooling that measures their behavior under load. The role sets the data plane’s multi-quarter technical direction, establishes standards for other teams, leads initiatives that keep the platform fast and correct as it scales, and influences platform direction with engineering leadership and product teams. The position is hybrid, requiring on-site work Tuesdays and Thursdays. In California, Tuesdays are on-site in San Francisco and Thursdays in San Jose; in New York City, both days are on-site in the NYC office. The application window is expected to close on 11/06/2026.

Requirements

Bachelor’s degree with 8+ years of related experience, or a master’s degree with 6+ years, or a Ph.D. with 3+ years, in Computer Science, Software Engineering, or a related field.
At least 6 years building and/or operating data-intensive backend services and/or platforms.
Technical leadership experience, including setting technical direction, driving multi-quarter initiatives, and/or influencing decisions beyond the immediate scope.
Experience designing, operating, and/or delivering highly scalable, reliable, production-grade data-intensive platforms.
Experience designing large-scale distributed systems and solving scalability, availability, performance, reliability, and/or fault-tolerance problems.
Backend software engineering experience with one or more of Go, Java, Rust, C++, and Python.
Experience with cloud-native technologies, containerized environments such as Kubernetes, and public cloud platforms such as AWS or GCP.

Nice To Haves

Performance engineering experience, including profiling, benchmarking, and load testing real systems and applying the results to capacity, design, and cost decisions.
Production-scale operation and tuning of both an OLTP database (such as PostgreSQL or MySQL) and an analytical, columnar, or time-series store (such as ClickHouse, Druid, BigQuery, or Snowflake), including schema design, indexing, query tuning, and migration safety.
Deep production experience with streaming or queueing systems such as Kafka, RabbitMQ, Pulsar, or Kinesis, including partitioning, consumer-group semantics, delivery guarantees, backlog handling, and dead-letter handling.
Experience scaling data-processing compute, including queue consumers, asynchronous task workers, or streaming jobs, with concurrency tuning, batching, backpressure, and sustained-load throughput behavior.
Deep experience running ClickHouse or a comparable columnar store at scale, including sharding and replication topology, materialized views, merge and mutation behavior, and retention and TTL mechanics.
Experience with a platform-scope capacity model or FinOps practice, including cost per unit of telemetry, cardinality governance, quotas, or rate-limit design.
Experience designing multi-tenant isolation and noisy-neighbor mitigation in shared data systems.
Experience leading a significant production data migration or storage-engine transition without customer-visible impact.
Experience defining SLOs for data services and driving an organization to meet them.
Experience with backup and restore, tested disaster-recovery drills against stated RPO/RTO, and data retention or deletion compliance such as GDPR/DSR hard delete.
Experience building observability instrumentation and pipelines, such as OpenTelemetry, collectors, and metrics or tracing backends.
Experience building or operating performance tooling for other engineers, such as load-test harnesses, continuous profiling and flame-graph workflows, or benchmarking suites.
Experience with distributed task frameworks and worker orchestration, such as Celery, Temporal, Flink, or custom consumer fleets, at production scale.
Familiarity with streaming databases, stream-processing frameworks, or distributed query engines such as RisingWave, Flink, Spark Streaming, or Trino/Presto, and with model-serving infrastructure.
Experience supporting stateful systems in both cloud/SaaS and air-gapped or on-premises deployments.
Experience mentoring senior engineers and raising engineering standards across multiple teams.
Strong communication skills, including translating performance, capacity, and cost findings into clear recommendations for engineering leadership and product partners.

Responsibilities

Define and drive the multi-quarter technical roadmap for the data platform, including storage, streaming, compute, and measurement tooling.
Lead data-plane architecture and evolution, including storage-engine selection, sharding and tenancy models, and control/data-plane boundaries.
Establish platform-wide standards for schema design, migration safety, and data retention, and lead the review process that enforces them.
Lead capacity and performance modeling and define service-level objectives (SLOs).
Lead scalability and performance initiatives across data stores, streaming pipelines, and distributed worker fleets.
Drive cost efficiency, including cost per unit of telemetry, cost attribution, quotas, and rate limits.
Set the direction for multi-tenant isolation to prevent one tenant from degrading another.
Design and build internal frameworks and performance tools for load testing, profiling, and benchmarking.
Establish platform observability standards so signals are correct, complete, and affordable.
Lead production investigations and drive systemic remediation rather than isolated fixes.
Make and document technology-selection and build-versus-buy decisions, including cost, risk, and migration analysis.
Partner with engineering leadership to influence platform direction and investment, and represent the data platform to product teams.
Mentor engineers and raise engineering standards through design reviews, technical standards, and documentation.

Benefits

Medical insurance
Dental insurance
Vision insurance
401(k) plan with Cisco matching contribution
Paid parental leave
Short- and long-term disability coverage
Basic life insurance
Paid holidays
Floating holiday for non-exempt employees
Paid birthday day off
Paid year-end holiday shutdown
Personal wellness days
Flexible vacation time off for eligible exempt employees
Paid vacation time for non-exempt employees
Paid sick time
Additional paid time away may be requested for critical or emergency family issues
Optional paid volunteer days
Annual bonuses for eligible non-sales roles
Potential grants of Cisco restricted stock units