Senior Fleet Intelligence Analyst

Salary Range: 130000 to 150000 (Currency: USD) (Pay period: per-year-salary)

Responsibilities

Own and operate Gridware's fleet triage pipeline for device health issues, intaking signals from telemetry, monitoring, field reports, and customer feedback, and routing them through a tiered prioritization framework.
Define and continuously tune detection logic, thresholds, and alerting rules that distinguish signal from noise across device health, connectivity, configuration, and environmental data.
Maintain a tiered triage approach (P0–P3) with clear entry criteria, SLAs, ownership, and escalation paths across hardware, firmware, and connectivity stakeholders.
Build dashboards and queries that surface emerging trends — shifts in last-seen, connectivity degradation, configuration drift, anomalous failure clusters — before they reach incident severity.
Investigate ambiguous fleet signals to determine scope, impact, and likely owner across the Gridscope and connectivity hardware programs; produce structured triage write-ups that enable fast cross-functional action.
Lead postmortems end-to-end: facilitate blameless reviews, reconstruct incident timelines, drive root cause analysis, and own action items through to closure.
Track triage and incident metrics (time-to-detect, time-to-acknowledge, false positive rate, repeat-issue rate) and use them to iterate on the pipeline.
Document triage playbooks, runbooks, and decision trees so the process scales beyond any one person.

Required Skills

Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, or related field.
5+ years in a data-focused or operations-focused role (Data Analyst, Operations Analyst, Site Reliability Analyst, or similar) where triage, prioritization, or incident response was a core responsibility.
Proficiency in SQL and Python for querying telemetry data and automating triage workflows.
Demonstrated experience designing prioritization frameworks, alerting logic, or triage pipelines in high-signal environments.
Strong analytical judgment for distinguishing meaningful signal from noise in noisy, real-world data.
Excellent written communication, with a track record of producing concise, structured issue summaries and postmortem documents.
Comfort facilitating cross-functional discussions, including blameless postmortems with engineering, firmware, and operations stakeholders.

Bonus Skills

Experience leading postmortems or incident reviews for IoT fleets, distributed systems, or large-scale hardware deployments.
Familiarity with Databricks, PySpark, Pandas, and observability tools (Looker, Grafana, Datadog).
Exposure to time-series telemetry, anomaly detection, and SLO/SLA design.
Experience with power-constrained, solar-powered, or communication-constrained connected devices.
A passion for sustainability, clean tech, or the energy industry.