Responsibilities
- Lead customers in the strategic application of Honeycomb and Observability practices to meet their stated technical and business goals, including shaping how their telemetry data is structured, governed, and used across their organization
- Partner with Customer Success Managers and Account Executives to articulate the Honeycomb value proposition, vision, and strategy at the executive and technical levels
- Act as a trusted advisor on telemetry schema design and data modeling, helping customers think through how to structure events, attributes, and relationships so their data is queryable, meaningful, and durable over time
- Become a subject-matter expert in the practice of Sampling and the operations of our Refinery sampling, advising customers on sampling strategies that balance cost, fidelity, and operational insight
- Work hands-on with, teach, coach, and mentor engineering teams and leaders in Observability, SRE concepts, and instrumentation best practices
- Advise customers on how to establish and evolve telemetry ownership and standards within their engineering organizations, including how to build internal documentation, naming conventions, and attribution practices that scale
- Troubleshoot and develop both technical and sociotechnical solutions to customer issues in ways that discrete roles (like Support and Engineering teams) cannot
- Create high-quality, reusable content including trainings, talks, blog posts, white papers, demos, and reference architectures
- Represent the voice of the customer in internal meetings with Engineering and Product Management, bringing pattern-level insights from the field
- Stay current on Honeycomb technologies, product offerings, and the broader observability ecosystem
Requirements
- Deep understanding of OpenTelemetry, its projects, components, SDKs, and ecosystem, along with the ability to guide customers through complex instrumentation decisions
- Strong intuition for how telemetry data should be modeled and organized: what makes an event schema useful vs. noisy, how to think about cardinality, and how to design for long-term queryability
- The ability to understand application's architecture and flow well enough to instrument it effectively and advise others doing the same
- Working knowledge of popular cloud platforms (AWS, GCP, or Azure), Infrastructure-as-Code tooling (Terraform, Kubernetes, Helm), and CI/CD platforms and practices (CircleCI, GitHub Actions, etc.)
- Previous experience in Software Development or System Operations, with a strong preference for candidates who have worked on distributed systems at scale
- Fluency in at least one of: Ruby, Python, Go, JavaScript, Java, or .NET, familiarity with multiple languages and/or frameworks is a strong plus
- Excellent written and verbal technical communication skills, with the ability to tailor depth and framing for both engineering teams and technical leadership
Nice to Have
- Previous experience in Customer Success, Technical Account Management, Sales Engineering, or Consulting
- Deep understanding of Distributed Tracing concepts (Context Propagation, Sampling, Visualization, etc.)
- Experience helping engineering organizations define internal observability standards, tagging taxonomies, or telemetry governance practices
- Public speaking experience, conference talks, internal tech talks, webinars, etc.
