Operations Data Engineering Analyst

Operations Data Engineering Analyst Monitoring & Diagnostics (M&D) JOB SUMMARY This position will function as part of the Southern Power Monitoring & Diagnostics (M&D) Center, which provides remote monitoring and diagnostic support to the SPC fleet of gas, solar, wind, and energy storage assets. The Operations Data Engineering Analyst supports both operational data infrastructure and AI/ML data readiness. The role assists the PI System Administrator with daily operation, maintenance, and expansion/migration of SPC’s AVEVA PI and AspenTech IP.21 historian environments, including tag management, Asset Framework (AF) configuration, analytics deployment, PI Vision development, data quality monitoring, and proactive remediation. The role also extracts, transforms, curates, and delivers clean, structured datasets from PI and IP.21 into downstream data engineering platforms such as Databricks to support M&D’s growing AI and machine learning portfolio, including iSight anomaly detection, predictive analytics models, and AI agents. In short, this role owns the data journey from raw sensor ingestion in PI through curated, AI-ready datasets — ensuring the M&D team always has trusted, high-quality, well-engineered data to power both real-time monitoring and advanced analytics. This position will closely interface with the Aveva PI/ AspenTech IP.21 System Administrator, M&D Analysts, AI/ML Analysts, Renewable Performance Engineers, Renewable, Gas, and Commercial Operations, the SPC Technology Organization, SCADA teams, and plant personnel. MAJOR JOB RESPONSIBILITIES PI/IP.21 System Support Tag Management — Support the PI/IP.21 Administrator in the creation, modification, scaling, and decommissioning of PI/IP.21 tags across gas, solar, wind, and energy storage assets. Ensure tag naming conventions, point types, and compression settings are consistent with fleet-wide standards. Asset Framework (AF) Configuration — Create, modify, and delete AF elements, attributes, templates, and hierarchies to reflect fleet changes (new sites, equipment swaps, decommissions). Maintain AF structure integrity across all OEMs (solar inverters, wind turbines, gas turbines, batteries, and BOP equipment). AF Analytics Deployment — Develop, test, and deploy PI AF Analytics (calculated attributes, rollup expressions, event frames) in test and production environments. Validate analytic outputs against expected results prior to production deployment. Data Quality Monitoring & Proactive Remediation — Continuously monitor data quality across PI and IP.21 platforms — identifying stale tags, flatlined signals, bad values, communication failures, scaling errors, and missing data. Proactively remediate issues before they impact downstream analytics, dashboards, or AI models. Support data surrogation processes where needed. PI Vision Development & Maintenance — Design, develop, and maintain real-time PI Vision screens and dashboards for fleet monitoring, equipment health, data quality, and KPI tracking. Update displays as new sites are onboarded or fleet configurations change. Site Onboarding Support — Assist the PI/IP.21 Administrator with integrating new generation and storage sites into the PI/IP.21 System, including interface/connector configuration, tag provisioning, AF buildout, initial data validation, and PI Vision screen creation. Data Query Support for Other Teams — Serve as a resource for operations, performance, and analytics teams who need to extract data from PI/IP.21. Provide support and guidance using PI DataLink, IP.21 Excel Connector, Python, SQL, PI Web API, and PI Connect to enable self-service data access and integration with downstream tools. Troubleshooting — Assist in diagnosing and resolving data flow issues, interface communication failures, archive gaps, and system errors within the PI and IP.21 environments. Escalate infrastructure-level issues to the PI/IP.21 Administrator or IT as appropriate. Data Engineering & AI/ML