Senior Staff Software Engineer (Data Platform, Kubernetes, Distributed Systems, Federal)

Join our Data Platform Engineering organization as a Senior Staff Software Engineer. You will lead the design and delivery of shared, multi-tenant platform services on Kubernetes, acting as the technical anchor for their availability, resilience, and operating model. You will also mentor mid-level and junior engineers and raise the engineering bar through code reviews, design feedback, and pairing.

- Lead the design and delivery of shared, multi-tenant platform services, including Postgres, queueing/streaming, and key-value stores, on Kubernetes. - Act as the technical lead on major initiatives within the team, breaking down ambiguous problems into clear, executable designs with explicit availability, durability, and cost targets. - Mentor mid-level and junior engineers, raising the engineering bar through code reviews, design feedback, and pairing, particularly around distributed-systems and data-service design.

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