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California, United States
Hybrid
We're looking for a self-motivated Senior Software Engineer to join the Platform team that powers all of SnapLogic's services. You'll work across the stack to make our platform resilient, performant, and able to scale with our enterprise customers — from the services that run customer pipelines, to the data layer that backs them, to the operational tooling that keeps it healthy in production.
This is a generalist role. You'll go deep where the work demands it, but we expect every Platform engineer to build end-to-end understanding of the systems we operate. SnapLogic operates ~50 MongoDB clusters across production and test environments, with 60TB+ of data, so engineers comfortable with query profiling, index tuning, and hands-on database work will find plenty to own — but database work is one area among many, not a separate track.
You take a deep sense of ownership, accountability, and pride in what you ship. You're proficient in at least one language and willing to learn whatever the problem requires.
This is a hybrid role based at our HQ in San Mateo, CA with the requirement to work in the office two days per week.
Design, build, and operate services and infrastructure that make up SnapLogic's control plane
Take end-to-end ownership: from design through production rollout and monitoring
Improve platform reliability, performance, and scalability — across services, data layer, and dependencies
Investigate and resolve production issues, then turn the fix into a durable improvement (better tests, observability, automation, or design changes)
Contribute to our data-layer work as needed: query and index tuning, schema/access pattern reviews, shard and cluster operations, capacity planning
Partner with other Platform engineers, SRE, and application teams to keep us on our zero-downtime SLA
Raise the bar on engineering quality — code review, design review, mentoring peers
5+ years building and operating production backend systems
Strong programming fundamentals, ideally in Java or Python; comfort picking up new languages and stacks
Experience operating distributed systems in production — debugging, profiling, capacity planning, incident response
Track record of taking features from design to production and owning them after launch
Solid grasp of databases (relational or NoSQL): query performance, indexing, schema design trade-offs
Excellent design, code, and written communication skills
B.S. in Computer Science, Computer Engineering, or equivalent practical experience
Hands-on experience operating MongoDB (or another NoSQL database) at scale — sharding, replica sets, query profiling, index tuning
Experience with cloud infrastructure (AWS preferred), containers, and CI/CD
Familiarity with observability tooling (metrics, tracing, structured logs) and SRE practices
