Senior Staff Software Engineer - Data Platform - Kubernetes - Distributed Systems - Federal

Description

You will join the Data Platform Engineering organization as a Senior Staff Software Engineer (IC5 Level), working as a hands-on technical lead.

The role supports the company's US Regulated Markets.

The work centres on shared, multi-tenant platform services for managed Postgres, queueing and streaming, and key-value or cache stores. These run on Kubernetes across a large global fleet, and product teams across the company rely on them.

The position is hybrid. You will work from a the company office location for 2 days per week. Offices are in San Francisco, CA; Pleasanton, CA; Santa Clara, CA; San Diego, CA; and Kirkland, WA.

Responsibilities

• Lead the design and delivery of the shared platform services, from design through production operation.
• Turn vague problems, such as offering highly available Postgres to every cluster or letting the queueing tier survive a zone loss, into clear designs with explicit availability, durability, and cost targets.
• Define high availability, failover, disaster recovery, and multi-region architecture for the services you own.
• Build Kubernetes-native automation, including operators, controllers, CRDs, and self-service APIs, that provisions, scales, upgrades, and fails over services without manual intervention.
• Work with principal and distinguished engineers to keep your work aligned with the wider platform architecture and standards.
• Work with product teams to agree on consumption contracts, tenancy models, and SLOs for shared services.
• Identify technical risks early and drive them to resolution, focusing on reliability, scalability, and operability. Lead failure-mode analysis, game days, and post-incident reviews for stateful systems.
• Spend significant time hands-on, designing, coding, and reviewing core systems such as operators, controllers, infrastructure automation, and platform services.
• Mentor mid-level and junior engineers through code reviews, design feedback, and pairing, especially on distributed systems and data service design.

Requirements

• Experience using AI in engineering or platform work, or thoughtful analysis of its effect on how infrastructure is built and run. This can include AI-powered tooling, automating operational workflows, agentic systems for fleet visibility and operations, or similar.
• 12+ years of software development experience with a Bachelor's degree, or 8+ years with a Master's degree, or 5+ years with a PhD, or equivalent work experience.
• 8+ years building production software, including solid experience operating distributed systems and running stateful workloads on Kubernetes at scale.
• A record of leading the design and delivery of at least one shared, multi-tenant infrastructure service used widely by other teams. Examples include a relational database service (Postgres or similar), a message queue or streaming platform (Kafka, NATS, RabbitMQ, or similar), or a key-value or cache service (Redis, Valkey, etcd, or similar). Include its HA, failover, and operating model.
• Deep understanding of high availability and failure handling: replication topologies, leader election, quorum and consensus, split-brain avoidance, backup and restore, point-in-time recovery, and designing to explicit RPO/RTO and durability targets.
• Strong system design skills. You reason rigorously about consistency models, partitioning and rebalancing, capacity planning, tenant isolation, and noisy-neighbor mitigation, and explain trade-offs clearly to engineers and stakeholders.
• Hands-on experience with at least one major hyperscaler (AWS, Azure, or GCP), including its core compute, networking, storage, and IAM primitives.
• Strong working knowledge of containers and Kubernetes, including stateful primitives such as StatefulSets, CSI and persistent storage, PDBs, and topology spread. Also CI/CD, GitOps-based delivery, and infrastructure-as-code.
• Strong programming skills in Go, or strong systems-language skills with willingness to work mainly in Go.
• Helpful: experience building or extending Kubernetes operators for stateful systems, such as CloudNativePG, Zalando or Crunchy Postgres operators, Strimzi, or Redis/Valkey operators, and a view on when to adopt an existing operator versus build one.
• Helpful: deep expertise in one target system. For Postgres: WAL, streaming and logical replication, vacuum, PgBouncer or PgCat pooling, and major-version upgrades. For Kafka or NATS: partitioning, ISR and replication, exactly-once semantics, and consumer scaling. For Redis or Valkey: cluster mode, persistence, eviction, and hot-key handling.
• Helpful: experience running data services across multiple regions or clusters, including cross-region replication, failover orchestration, and DR testing.
• Helpful: experience with zero-downtime upgrades, schema and data migrations, and fleet-wide rollouts of stateful services.
• Helpful: experience with observability and SLOs for stateful systems, covering replication lag, saturation, tail latency, and error budgets, plus capacity and cost management for shared infrastructure.
• Helpful: experience designing multi-tenancy, including quotas, isolation, chargeback or showback, and self-service provisioning APIs or CRDs.
• Helpful: experience with container networking (CNI) or a service mesh, and with workload identity, mTLS, and secrets management for data services.
• Helpful: experience with managed Kubernetes (EKS, AKS, or GKE), managed data services (RDS or Aurora, Cloud SQL, MSK, or ElastiCache), and infrastructure-as-code tools such as Terraform or Crossplane.

Conditions

Base pay is $149,800 - $262,200 for positions in this location, plus equity where applicable, variable or incentive compensation, and benefits.

The base pay shown is a guideline. Individual total compensation depends on qualifications, skill level, competencies, and work location. Pay also depends on the geographic location of the role and may change with it.

Sales positions generally offer a competitive On Target Earnings incentive structure.

Work persona (flexible, remote, or required in office) is set by the nature of the work and the assigned work location. The company may check the distance between your home and the nearest office with a third-party service to confirm eligibility.

Benefits

• Health plans, including flexible spending accounts.
• 401(k) plan with company match.
• Employee stock purchase plan (ESPP).
• Matching donations.
• Flexible time away plan and family leave programs.