We source, vet, and manage hiring so you can meet qualified candidates in days, not months. Strong English, U.S. time zone overlap, and compliant hiring built in.
.svg){kind=logo}
yq is a command-line YAML processor, analogous to jq for JSON. It lets you parse, filter, transform, and extract data from YAML using similar syntax to jq. yq has become essential for DevOps engineers working with Kubernetes, GitOps, and infrastructure-as-code systems.
Kubernetes YAML files are ubiquitous in modern infrastructure. yq is how you programmatically query and modify those files. Need to extract a service's port? yq. Patch all ConfigMaps in directory? yq. Validate YAML structure in CI/CD? yq. It's become table stakes for any engineer managing Kubernetes.
yq is a YAML processor mirroring jq closely. Syntax very similar, ecosystem has specific patterns: patching Kubernetes manifests, extracting metadata, validating schema, GitOps integration. Multiple implementations exist (go-yq, python-yq). Modern standard is go-yq: fast and feature-complete. GitHub stars for yq: 10K+ and growing. Stack Overflow mentions exploding as Kubernetes adoption grows.
You need yq expertise when managing large Kubernetes clusters with complex manifests; building GitOps pipelines modifying YAML; or automating infrastructure-as-code workflows. Most yq work is DevOps, platform engineering, or SRE.
yq is rarely standalone. You're hiring DevOps or platform engineers with strong yq expertise. Look for engineers writing sophisticated yq scripts as part of Kubernetes automation.
Must-Have Skills: Solid yq knowledge. Understand YAML path expressions, filters, transformations, piping. Write complex yq filters for real Kubernetes manifests. Deep Kubernetes knowledge (understand selectors, labels, namespaces).
Seniority Breakdown: Junior (1-2 years): Understands yq basics, field access, simple filtering. Written basic patches but needs guidance. Mid-level (3-5 years): Writes sophisticated yq for production Kubernetes. Designs manifests working with yq, understands piping, optimizes. Senior (5+ years): Architect-level. Optimized Kubernetes YAML at scale, built custom yq tooling, mentored. Deep YAML knowledge.
1. Tell me about a complex Kubernetes YAML transformation with yq. What was the use case? 2. Describe patching or validating Kubernetes manifests at scale using yq.
1. Explain yq path expressions. How do you access nested fields in complex Kubernetes resources? 2. Write a yq filter extracting all environment variable names from all containers in Kubernetes Deployment. 3. How do you modify multiple manifests in directory using yq in shell loop?
Task: You have 5 Kubernetes Service manifests in directory. Extract all names and ports, validate all have selectors, patch all to add specific label. Show the script. Evaluate correctness, real-world problem-solving, shell integration.
Latin America (2026): Junior: $35K-$48K/year. Mid-level: $52K-$75K/year. Senior: $78K-$115K/year. United States (2026): Junior: $75K-$105K/year. Mid-level: $110K-$160K/year. Senior: $160K-$220K/year. yq expertise is part of DevOps and platform engineering compensation. Salaries reflect Kubernetes and infrastructure skills.
LatAm DevOps and platform engineering teams are proficient in yq. Brazil, Argentina, Colombia have growing Kubernetes adoption, creating demand for YAML manipulation and GitOps skills. Most modern LatAm infrastructure teams use yq as part of standard tooling. Cost savings exceptional: $52K-$75K/year for mid-level vs $110K-$160K/year for US. Time zone overlap excellent. These engineers combine deep Kubernetes knowledge with strong yq skills.
We identify platform engineering and DevOps engineers with strong yq expertise and Kubernetes knowledge. You define infrastructure automation needs, we match from pre-vetted network. Within days you're interviewing candidates understanding YAML deeply and building automation frameworks.
Yes. Syntax very similar. If you know jq, yq takes 1-2 weeks to learn. Engineers often know both.
Yes. yq pipes seamlessly into grep, xargs, other Unix tools for batch Kubernetes operations.
kubectl is for Kubernetes API operations. yq is for YAML file manipulation. Complementary. yq works offline on manifests; kubectl works against live clusters.
Yes, efficiently. yq written in Go, handles large manifests well.
Helpful but not required. Syntax similar, so jq knowledge accelerates learning. Most engineers know both.
Yes. Platform engineering work often project-based. Short-term engagements possible.
Technical assessment (yq and Kubernetes fundamentals), portfolio review (automation scripts and GitOps projects), reference checks.
Yes. yq essential for GitOps workflows (ArgoCD, Flux). Our engineers often have GitOps platform experience.
Most yq engineers know jq. We can match engineers fluent in both.
Yes. Write validation scripts using yq filters. Our engineers design frameworks.
Yes. For YAML-based IaC. Combined with Kustomize or Helm, yq is powerful for transformation.
