What is The Role
As a Consulting Architect – Observability, you will play a pivotal role in helping our customers realize the value of Elastic's Solutions. Acting as a trusted technical advisor, you will work with enterprises to design, deliver, and scale architectures that improve application performance, infrastructure visibility, and end-user experience.
You'll collaborate with Elastic's Professional Services, Engineering, Product, and Sales teams to accelerate adoption of the Elastic Observability platform, ensuring customers maximize the value of their data while achieving business outcomes. This is a highly impactful role, with opportunities to guide strategy, lead complex implementations, and mentor both customers and teammates.
What You Will Be Doing
- Translate business and technical requirements into scalable, outcome-driven solutions built on the Elastic Stack.
- Partnering and guiding our largest Telecommunications focussed customer in Japan to maximise the value they get from their Elastic deployments, and reimagine what other opportunities they could explore
- Lead end-to-end delivery of customer engagements — from discovery and design through implementation, enablement, and optimization.
- Partner with customers to architect, deploy, and operationalize Elastic solutions that drive measurable value and adoption.
- Provide technical oversight, guidance, and enablement to customers and teammates throughout project lifecycles.
- Collaborate cross-functionally with Sales, Product, Engineering, and Support to ensure successful outcomes and continuous improvement.
- Capture and share best practices, lessons learned, and solution patterns across the Elastic Services community.
- Contribute to internal enablement, mentoring, and a culture of continuous learning and collaboration
- Guide customers in using Elastic Agents, Beats, Logstash time-series data ingestion, stream processing, and normalization, and related technologies.
- Design and implement custom dashboards, visualizations, and alerting for critical observability use cases in Kibana.
- Optimize ingestion pipelines for performance, scalability, and resiliency at enterprise scale.
What You Bring
- 5+ years as a consultant, architect, or engineer with expertise in observability, monitoring, or related domains.
- Expertise in the Telecommunications domain, especially with Mobile networks and devices.
- Strong experience with time-series data ingestion and processing, including pipelines with Elastic Agents, Beats, and Logstash.
- Knowledge of messaging queues (Kafka, Redis) and ingestion optimization strategies.
- Understanding of observability concepts like distributed tracing, metrics pipelines, log aggregation, anomaly detection, SLOs/SLIs.
- Experience with one or more: Kubernetes, cloud platforms (AWS, Azure, GCP), or infrastructure as code.
- Familiarity with Elastic Common Schema (ECS), data parsing, and normalization.
- Proven experience deploying Elastic Observability (APM, UEM, logs, metrics, infra, network monitoring) or similar solutions at enterprise scale.
- Hands-on expertise in distributed systems and large-scale infrastructure.
- Ability to design and build dashboards, visualizations, and alerting thresholds that drive actionable insights.
- Experience with Kubernetes, Linux, Java, databases, Docker, AWS/Azure/GCP, VMs, Lucene.
- Strong communication and presentation skills, with experience engaging directly with customers.
- Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field, or equivalent experience.
- Comfortable working in highly distributed teams, both remote and on-site when needed.
- May require significant travel to customer sites to support engagements and solution implementations; candidates should be comfortable with varying levels of travel based on business needs.
Bonus Points
- Elastic Certified Engineer certification or deep expertise with Elasticsearch/Lucene.
- Big 4 consulting or equivalent professional services experience.
- Experience with Ansible, Terraform, JavaScript, ECK/Kubernetes.
- Knowledge of machine learning or AI applied to observability.
- Experience contributing to open-source project or documentation.
- Public speaking experience at conferences, meetups, or enterprise workshops.
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