Product Manager - Log Management bei Observe, Inc.
Observe, Inc. · San Mateo, Vereinigte Staaten Von Amerika · Onsite
- Senior
- Optionales Büro in San Mateo
About Observe
Observe is re-imagining observability for the cloud era. We deliver open, scalable observability by collecting logs, metrics, traces directly in a cloud data lake, linking every event in a real-time knowledge graph, and using a modern columnar analytics database to query it all. This lake-first architecture eliminates costly upfront indexing, keeps all telemetry in low-cost object storage, and lets engineering teams correlate petabytes of data in real-time. Our customers troubleshoot faster while cutting observability spend by as much as 70 percent.
The role
Log Management is both our fastest-growing workload and the first workload most prospects adopt. As Product Manager for Logs you will own the end-to-end experience: ingest, search, indexing-on-demand, alerting, dashboard, and reporting. Your mission: make Observe the natural upgrade from Splunk, Elastic, Datadog, or home-grown solutions. You will validate problems, align the roadmap, ship furiously, and drive adoption.
What you’ll do
Define and maintain a 12-month roadmap for log ingest, search, indexing-on-demand, alerting, dashboard, and reporting.
Validate problem statements through frequent customer interviews, win/loss reviews, and usage data analysis.
Partner daily with Engineering and Design to scope, ship, and iterate in small, measurable slices.
Set and track key product and business metrics; adjust priorities based on evidence.
Drive launches by supplying positioning, demos, and pricing/packaging input to Sales and Marketing.
Represent the Logs product vision and roadmap internally and externally, aligning stakeholders on direction.
What we’re looking for
5+ years of product-management experience in log management, observability, SIEM, or large-scale data platforms.
Hands-on familiarity with tools such as Splunk, Elasticsearch, or Grafana, and the ability to self-serve basic data analysis.
Technical depth in distributed systems, cloud storage, or data-lake architectures; comfortable discussing trade-offs with senior engineers.
Bias for evidence and iteration; thrive in the fast-paced, constantly changing environment of a growth-stage startup.
Strong written and verbal communication; comfortable with enterprise POCs and technical evaluations.
