data, and that footprint is a core part of the charter.
You will derive a roadmap that balances customer commitments, technical debt, and
platform innovation, and you will be judged on reliability and scale as much as on
delivery. You are also the eyes and ears on platform health for the wider engineering
organization, working with SRE, application teams, support, and company leadership.
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.
- What You'll Do:
- Platform Ownership & Architecture
You own the services that make up SnapLogic's control plane. You set the architectural direction for reliability, performance, and scalability across services, the data layer, and upstream dependencies. You review designs for criticalcomponents, you make the call on build versus buy, and you keep a clear view of risk versus reward on every production change. You decide how much of your own time goes to coding and code review, and you keep enough hands-on depth to lead the work credibly.
Engineering Leadership & Team Building
You have led and managed engineering teams, and you think constantly about team productivity, quality, and health. You own hiring for the team, including the forecast and budget, recruiting strong engineers, and promoting and growing the people already here. You organize the team to make impactful changes, you delegate technical ownership over subject matter areas, you establish leads and empower them to mentor their own reports, and you give direct, constructive feedback. You run regular one-on-ones, advocate for career growth, and resolve conflict early.
Reliability, SRE, & Production Support
You are accountable for the zero-downtime SLA. You drive root cause analysis, own SRE process improvements, and make sure those processes are actually followed. You keep your eyes on production at all times and pull in resources before widespread impact is felt. You turn every incident into a durable improvement: better tests, observability, automation, or a design change. You manage support escalations, stay in close contact with the support manager, and join customer escalation calls when needed.
Cloud-Native Infrastructure & GitOps
You understand Kubernetes well beyond deploying workloads: operators and custom resources, policy enforcement, networking, IAM integration, and capacity. You lead the ongoing move of legacy EC2-based services onto Kubernetes without putting availability at risk. You treat developer self-service, environments on demand and an internal developer portal as a product your team owns.
Data Layer at Scale
You own the strategy for a MongoDB footprint of roughly 50 clusters and more than 60TB of data. That covers query and index tuning, schema and access pattern reviews, shard and replica set operations, upgrade and migration planning, and capacity planning against growth. You make sure this expertise is spread across the team rather than concentrated in one or two people.
AI Leadership & Engineering Productivity
You champion the adoption of AI throughout the Software Development Life Cycle, using AI as a force multiplier for engineering excellence, delivery speed, and product quality. You have hands-on experience designing, building, and deploying AI agents that automate engineering workflows and raise developer productivity. You advocate for AI-leveraged development while holding the line on engineering best practices, security, and quality.
Communication & Cross-Functional Partnership
You work directly with application teams, SRE, support, and the field to set and meet expectations on platform capability and platform health. You translate platform work into terms the business understands, document your processes, and keep your team informed. When customers need to hear from engineering, you are a credible spokesperson. What We’re Looking For: 10+ years building and operating production backend systems, including enterprise SaaS or PaaS
5+ years leading and managing engineering teams, including on-shore and off-shore teams
Strong programming fundamentals, ideally in Java and/or Python, with the comfort to pick up new languages and stacks
Deep experience operating distributed systems in production: debugging, profiling, capacity planning, and incident response
Track record of taking systems from design through production rollout and owning them after launch
Solid grasp of databases, relational or NoSQL, including query performance, indexing, and schema design trade-offs
Deep understanding of distributed systems, including HTTP protocols, distributed caching strategies, and observability
Experience being accountable for an availability SLA on a customer-facing platform
Hands-on experience running Kubernetes in production at scale, ideally Amazon EKS, including troubleshooting cluster, networking and workload issues
Experience with GitOps delivery (ArgoCD) and infrastructure as code (Terraform or equivalent)
- B.S. or M.S. in Computer Science, Computer Engineering, or equivalent practical experience
- Preferred Qualifications:
- Experience with cloud infrastructure, AWS preferred, containers, and CI/CD
Familiarity with observability tooling (metrics, tracing, structured logs) and SRE practices
Experience implementing continuous delivery and cloud deployment solutions
Multi-tenant public and private cloud experience
Hands-on experience operating MongoDB, or another NoSQL database, at scale: sharding, replica sets, query profiling, and index tuning
Agile project and release management
A record of accurate, fast decision making under production pressure
