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Snowflake is seeking a Senior Software Engineer to build the ingestion execution platform—a multi-tenant control plane that powers Snowflake's data ingestion products at petabyte scale. This is foundational infrastructure work: you will own the substrate that other ingestion teams depend on, handling pipeline lifecycle, durable work queues, orchestration, scheduling, monitoring, and cluster topology.
You will take hard distributed-systems problems from design through production and make neighboring product teams more successful. The role spans design, implementation, production deployment, and operational support. Key areas include multi-tenant isolation and fairness (quotas, backpressure, resource accounting, placement), reliability and observability (availability, latency, instrumentation), platform surface design (consistent APIs for product teams), control-plane scaling (concurrent pipelines, ingest volume, compute efficiency), and production operations including mentorship of junior engineers.
This is an end-to-end ownership role. You will influence adjacent teams, help sequence larger platform bets, and live with your code in production on a critical path. Snowflake emphasizes AI-native thinking and treating AI as a high-trust collaborator in problem-solving and development.
REQUIREMENTS:
- 3–6+ years building and operating large-scale distributed systems or cloud infrastructure in production; shipped something hard that other teams depend on (not just application features)
- Track record of end-to-end ownership: took ambiguous, cross-cutting problems from design through code to production; comfortable operating above your level and influencing adjacent teams
- Strong proficiency in Java (codebase is Java-first); C++ or systems-level experience a plus; write concurrent, failure-aware code with attention to invariants
- Experience in at least one of: multi-tenant control planes, durable queues and at-least-once processing, distributed locking/leases/membership, cluster scheduling, or streaming/ingest execution engines
- Instinct for correctness under failure: think carefully about crashes, retries, redelivery, and exclusive ownership
- Clear written and verbal communication; can write design docs for neighboring teams and hold technical arguments without ego
- BS, MS, or PhD in Computer Science, Computer Engineering, or equivalent practical experience
BONUS:
- Experience building internal platforms used by multiple product teams (orchestration, job/runtime frameworks, multi-tenant schedulers)
- Background in multi-tenant isolation and fairness (resource accounting, request throttling, quota systems, load-aware placement)
- Hands-on with transactional or consensus-backed metadata stores (etcd, ZooKeeper, Spanner-style systems)
- Familiarity with open table formats (Apache Iceberg, Delta Lake), Kafka-style streaming, or warehouse scheduling
- Performance work at scale (tail latency, memory/thread accounting, I/O batching, cost-per-unit efficiency)
- Used AI as a serious engineering collaborator (design review, debugging, test generation) and can demonstrate how it made you faster without lowering the bar
