Data Center Mechanical Data Analyst - Remote || W2

Hello,

Hope you are doing well,

Role: Data Center Mechanical Data Analyst || W2 only

Location: Remote

Top 3 Must-Have HARD Skills & Years of Experience

Data Analysis Experience (4+ years) Strong ability to analyze telemetry, identify trends, and interpret signals

Kusto (KQL) Working proficiency (can be developed further if strong in data analysis)

Grafana and/or Power BI Experience building dashboards and interpreting data insights

Note: Python experience is a plus but not required. Candidates with strong data analysis and data center/mechanical experience will be prioritized over deep scripting expertise.

Candidates must have data center or some mechanical experience

Role is remote

Top 3 Must-Have HARD Skills & Years of Experience

• Data Analysis Experience (4+ years) Strong ability to analyze telemetry, identify trends, and interpret signals
• Kusto (KQL) Working proficiency (can be developed further if strong in data analysis)
• Grafana and/or Power BI Experience building dashboards and interpreting data insights

Note: Python experience is a plus but not required. Candidates with strong data analysis and data center/mechanical experience will be prioritized over deep scripting expertise.

Key Requirements / Ideal Candidate Profile

We are seeking a strong communicator who can clearly articulate findings, collaborate cross-functionally, and provide concise updates during active investigations.

Candidates should have:

• 4+ years of relevant experience in data analysis, operations, or incident review
• Data center experience with a strong understanding of critical environments
• Background in Mechanical and/or Electrical systems, with:
  • Mechanical experience strongly preferred over electrical if one must be prioritized
• Ability to interpret telemetry signals and support incident investigations in high-availability environments
• Comfort working in fast-paced, high-visibility environments with cross-functional teams

Day-to-Day Responsibilities

Morning Routine

• Review overnight incidents, alerts, and telemetry signals
• Identify anomalies, trends, or issues requiring deeper investigation
• Prioritize workload based on urgency and impact

Active Investigation & Coordination

• Investigate incidents and abnormal signals (validate data, confirm accuracy, determine next steps)
• Partner with engineering, operations, and SMEs to gather context and validate findings
• Participate in team syncs and provide status updates

Communication & Documentation

• Provide clear, timely updates during investigations
• Summarize findings, risks, and recommended next steps
• Maintain strong communication with cross-functional teams and stakeholders

Data Hygiene & Tagging

• Ensure accurate incident tagging, classification, and metadata updates
• Identify and escalate data quality or signal gaps
• Support improvements to monitoring and detection logic

End-of-Day Wrap-Up

• Reassess incident queue and ensure ownership of open items
• Share concise status updates, blockers, and next steps

Technical & Functional Skills

• KQL querying for signal validation and telemetry analysis (preferred, not mandatory if strong in data analysis)
• Experience with Grafana and/or Power BI
• Familiarity with monitoring systems, telemetry pipelines, and alerting frameworks
• Strong analytical and problem-solving skills

Additional Preferred Background

• Experience in data center operations, critical environments, or site reliability
• Mechanical systems exposure (cooling, HVAC, infrastructure) strongly preferred
• Ability to work with ambiguous data and drive structured investigations

Performance Expectations

• Quality and accuracy of analysis
• Ability to meet deadlines and manage workload effectively
• Clear communication and documentation

Work Environment

• Remote
• Fast-moving, collaborative small v-team

Summary

The main function of this role is to analyze and interpret telemetry data, investigate incidents, and coordinate cross-team efforts to ensure accurate signal detection and operational excellence within a data center environment.

Thanks,

Sudhanshu Srivastava

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