GE eTerra

Role Overview This role requires a senior utility professional with extensive experience in electric transmission and distribution operations and deep familiarity with GE ETERRA GMS and EMS platforms used in live control center environments. The position focuses on helping utilities overcome fragmented operational visibility by aligning control room realities, operational data, and emerging AI capabilities. The successful candidate understands how operators actually run the grid—under normal conditions and during high stress events—and can translate those needs into practical data, integration, and analytics strategies that support better operational decisions.

Key Responsibilities

Grid Operations & Control Center Expertise

• Act as a trusted subject matter expert for transmission and distribution operations, including real time grid monitoring, switching activities, outage coordination, restoration planning, and control room procedures.
• Provide practical insight into how operators manage voltage conditions, equipment loading, alarms, contingencies, and coordination with neighboring utilities and market operators.

Operational Systems & Data Assessment

• Evaluate operational and enterprise systems across EMS, GMS, SCADA, DMS/ADMS, OMS, historians, asset platforms, market systems, and field technologies.
• Identify where system boundaries, data latency, or organizational handoffs limit operational awareness or delay effective decision making.

AI & Advanced Analytics Use Case Development

• Identify operational scenarios where AI and advanced analytics can support grid operations, including:

o Alarm prioritization and reduction of nuisance alarms o Detection of abnormal grid behavior o Correlation of events across transmission, distribution, and field systems o Improved awareness during outages, restorations, and abnormal operating conditions o Visibility into emerging asset and reliability risks Architecture & Data Strategy Collaboration

• Work with operations, OT, IT, and data teams to define secure and reliable data sharing patterns that support near real time operational insight without disrupting control system integrity.
• Translate operational requirements into analytics and AI needs, including data quality expectations, contextual tagging, event streams, model inputs, operator review points, and explainability considerations.