A Full Stack Reliability Engineer at Kohl's is an engineer who has a deep level of knowledge in systems, software engineering and associated automation, tooling and processes. They possess a breadth and depth of knowledge that allows them to iteratively improve the operability, observability, reliability, scalability and performance of the systems to reduce the operational overhead, reduce risks and simplify the ecosystem. They drive operational excellence across Kohl's by enabling Balanced Product Teams and other Partner Teams to up-level the health of their services in production, improve reliability, and empowering them to self-serve and run their services by having strong partnerships and continuous collaboration.
JOB RESPONSIBILITIES
Follows software lifecycle, driving reliability, observability, and efficiency across product teams within your domain
Identifies repeated toil and finds opportunities for automation and risk reduction
On-call on a rotation to respond to production incidents and conduct blameless retros and root-cause analysis (RCAs) to drive a culture of continuous improvements
Proactively identifies failures before it becomes an outage using chaos engineering techniques such as edge cases, failure modes, and DR
Advises on capacity planning and provides continuous assessments on systems behavior and consumption working towards optimization and cost savings
Works with product managers to identify and prioritize tech debt for reliability best practices (e.g. SLIs/SLOs/Error Budgets)
QUALIFICATIONS
REQUIRED
Bachelor's Degree or equivalent in MIS, Computer Science or related field
2+ years of experience in software development
Have strong programming skills in one or more languages - Java, Python, Go or Node.js
Experience working with one of major cloud platforms (GCP, AWS, or Azure)
PREFERRED
Experience in one of more Observability platforms - Dynatrace, Splunk, Prometheus, InfluxDB, Grafana, ELK or APM
Knowledge of application design patterns, event-driven architecture, database schemas, and testing strategies
Experience with large scale application troubleshooting and performance tuning
Knowledge and experience with continuous integration, continuous deployment, and test driven development
Experience in at least one PasS & Containers - Openshift, Cloud Foundry, Kubernetes or equivalent
Experience with one or more configuration management systems like Chef, Ansible, Puppet
Good understanding of systems architecture, UNIX internals, networking topologies, multi-cluster applications, multi-tenant platforms, and systems/network security
