Bachelor's degree in Computer Science, a related field, or equivalent practical experience
3+ years of professional software engineering experience building and operating data infra/backend systems, with a track record of shipping quality work quickly
A solid foundation in distributed systems or data infrastructure, and the drive to go deep
Experience owning a project or significant component end to end: driving the design, building it, shipping it, and running it in production
Strong technical communication, especially in writing, e.g., design docs, code review, async discussion across a distributed team
Sound judgment in technical tradeoffs, informed by real lessons from operating systems in production
High ownership and accountability
A desire to be at the forefront of the infrastructure powering AI-first analytics at thousands of companies
Languages: Go, C/C++, Python, and SQL
Distributed systems: sharding/partitioning, replication, distributed scheduling, work fanout/merge, consistent hashing
Storage & query engines: columnar formats (Arrow/Parquet or in-house equivalents), indexing, and compression
Caching: distributed file/block caches, admission and eviction policies, tiered storage
Performance engineering: profiling (pprof, perf), concurrency, memory management, benchmarking
Cloud & infra: GCP (GCS, GKE, Spanner) or equivalent AWS/Azure, Kubernetes
Reliability: observability (metrics, tracing, logging), SLOs, incident management
AI-augmented engineering: LLM tooling to accelerate development, triage, and operations