Observability Engineer
The Observability Engineer is responsible for helping migrate from SignalFX to Datadog stakeholders through a value-driven migration from legacy monitoring platforms (e.g., SignalFX/Splunk Observability Cloud) to modern observability solutions such as Datadog. This role emphasizes rationalization, optimization, and enablement—ensuring that migrated dashboards and metrics are cost-efficient.
Key Responsibilities:
- Assessment & Rationalization: Work with customers to help them decide which dashboards to migrate, refactor, or retire based on business impact.
- Datadog Optimization: Map legacy dashboards to Datadog's native templates and features. Leverage AWS integrations and out-of-the-box dashboards to reduce custom build effort.
- Stakeholder Enablement: Educate Infra, App, and DevOps teams on Datadog's capabilities and best practices. Ability to collaboratively train and document supporting long-term dashboard ownership.
Required Skills & Experience:
- Proven expertise in Datadog, including AWS integrations and dashboard templating.
- Experience with SignalFX/Splunk Observability Cloud and legacy monitoring paradigms.
- Experience working across Infra, App, and DevOps teams to create relevant metrics.
- Experience with applying SRE concepts.
- Strong understanding of AWS architecture and cloud-native observability.
- Strong understanding of monitoring distributed systems.
- Familiarity with OpenShift or Kubernetes.
- Familiarity with Ansible.
- Familiarity with Infrastructure-as-Code concepts.
- Familiarity with OpenTelemetry.
- 3 years of Python development experience.
- Excellent communication and stakeholder management skills.
Preferred Qualifications:
- Certifications in Datadog, AWS, or related observability platforms.
- Experience in enterprise-scale monitoring transformations.
Remote CST or EST time zone - NOT PST!
EEO: Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.