Senior Data Analyst, Fleet Triage & Operations

United States·San FranciscoFull-Timesenior

Data AnalystData

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About Gridware Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of…

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About Gridware

Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

The Data Analyst, Fleet Triage & Operations owns the front line of fleet issue detection, prioritization, and incident learning at the device health layer — sitting at the interface of Gridware's hardware programs, including Gridscope and our connectivity solutions. As the deployed fleet scales, telemetry volume grows faster than any team can manually inspect, and not all signals matter equally. This role separates signal from noise, ensures the right issues reach the right teams before they become incidents, and leads the postmortem process to make sure the same class of issue doesn't go undetected twice.

You'll design and operate a tiered triage pipeline, tune the detection logic that surfaces emerging device health issues, and facilitate postmortems end-to-end — from incident timeline reconstruction through action item closure. This is a highly cross-functional role that blends data analysis, operational rigor, and structured incident learning across hardware, firmware, and connectivity domains.

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.

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.

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.