Senior Data Analyst, Fleet Triage & Operations

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.