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Telemetry Technician
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Telemetry Technician in Mountain View, CA, on a 12+ month contract, offering a competitive pay rate. Key skills include data analysis (SQL, Python, R), visualization tools (Tableau, Grafana), and log analysis expertise.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
688
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ποΈ - Date
October 4, 2025
π - Duration
More than 6 months
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ποΈ - Location
Hybrid
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
Mountain View, CA
-
π§ - Skills detailed
#Regression #Looker #Plotly #Data Analysis #Splunk #R #Strategy #Tableau #Monitoring #Visualization #Elasticsearch #Logging #Datadog #Grafana #Python #SQL (Structured Query Language) #Microsoft Power BI #BI (Business Intelligence)
Role description
Title: QA Data Analyst & Telemetry Specialist
Location: Mountain View, CA
Duration: 12+Months contract
Job Description:
About the Role:
Weβre looking for a QA Data Analyst & Telemetry Specialist to help drive our product quality efforts through insightful data analysis, robust reporting, and close collaboration with engineering teams. This hybrid role combines skills in data analysis, log exploration, instrumentation design, and reporting.
Responsibilities:
β’ Data Analysis & Log Investigation
β’ Hunt down the right logs, trace product issues across environments, and analyze patterns in system behavior to support QA investigations and test coverage strategy.
β’ Instrumentation Partnership
β’ Collaborate with engineers to define, scope, and validate telemetry requirements to ensure the right data is being captured for quality signals.
β’ Dashboards & Visualization
β’ Design and maintain clear, role-specific dashboards that reflect test results, coverage trends, performance metrics, and release health.
β’ Assist QA and dev teams with root cause investigations using log data, traces, metrics, and real-world usage patterns.
β’ Partner with QA, Engineering, Product, and Data teams to align on what signals matter and how theyβre consumed across tools and stakeholders.
β’ Define and refine KPIs around bug trends, feature coverage, regressions, and release readiness to guide strategic QA direction.
β’ Strong hands-on experience with data analysis (SQL, Python, R, or similar)
β’ Skilled in producing clear visualizations (e.g., Superset, Plotly, Tableau, Looker, Grafana, Power BI)
β’ Able to write concise reports with actionable insights β weekly summaries, defect overviews, quality scorecards, etc.
β’ Familiar with log analysis tools (e.g., Sumologic, Splunk, Datadog, Kibana, ElasticSearch)
β’ Comfortable discussing and designing instrumentation/logging with engineers
β’ Familiarity with QA concepts, release validation, and production monitoring
β’ Strong communication skills; can adapt output to technical and non-technical audiences
Title: QA Data Analyst & Telemetry Specialist
Location: Mountain View, CA
Duration: 12+Months contract
Job Description:
About the Role:
Weβre looking for a QA Data Analyst & Telemetry Specialist to help drive our product quality efforts through insightful data analysis, robust reporting, and close collaboration with engineering teams. This hybrid role combines skills in data analysis, log exploration, instrumentation design, and reporting.
Responsibilities:
β’ Data Analysis & Log Investigation
β’ Hunt down the right logs, trace product issues across environments, and analyze patterns in system behavior to support QA investigations and test coverage strategy.
β’ Instrumentation Partnership
β’ Collaborate with engineers to define, scope, and validate telemetry requirements to ensure the right data is being captured for quality signals.
β’ Dashboards & Visualization
β’ Design and maintain clear, role-specific dashboards that reflect test results, coverage trends, performance metrics, and release health.
β’ Assist QA and dev teams with root cause investigations using log data, traces, metrics, and real-world usage patterns.
β’ Partner with QA, Engineering, Product, and Data teams to align on what signals matter and how theyβre consumed across tools and stakeholders.
β’ Define and refine KPIs around bug trends, feature coverage, regressions, and release readiness to guide strategic QA direction.
β’ Strong hands-on experience with data analysis (SQL, Python, R, or similar)
β’ Skilled in producing clear visualizations (e.g., Superset, Plotly, Tableau, Looker, Grafana, Power BI)
β’ Able to write concise reports with actionable insights β weekly summaries, defect overviews, quality scorecards, etc.
β’ Familiar with log analysis tools (e.g., Sumologic, Splunk, Datadog, Kibana, ElasticSearch)
β’ Comfortable discussing and designing instrumentation/logging with engineers
β’ Familiarity with QA concepts, release validation, and production monitoring
β’ Strong communication skills; can adapt output to technical and non-technical audiences