Power Systems & Data Engineer III

Electric Power Engineers is focused on shaping the grid of the future through advanced energy intelligence. In this role, you will support utility clients by delivering consulting services on distribution system modeling, planning, and data-driven analysis, ensuring informed decision-making in the evolving energy landscape.

Responsibilities:

• Perform distribution planning studies across multiple software platforms while applying planning criteria and conducting mitigation and alternatives analyses
• Evaluate the impacts of load growth and distributed energy resource (DER) interconnections, recommend cost-effective mitigation measures, and identify feasible alternatives
• Assess multi-year utility system plans in alignment with client objectives and state or jurisdictional requirements
• Conduct research related to the proliferation of DERs and advanced distribution technologies such as solar, wind, energy storage, electric vehicles, conservation voltage reduction, distribution automation, and system restoration
• Develop and maintain data-driven solutions for distribution system analysis, including data processing pipelines, analytical and simulation models, and visualization or decision-support tools
• Design and implement analytical tools, scripts, and workflows (Python- and/or SQL-based) to improve efficiency, automation, and reproducibility of studies
• Analyze historical distribution system data (e.g., AMI, SCADA, DER, EV data) to identify trends, anomalies, and planning insights
• Support the development of data standards, model validation processes, and integration between engineering tools and enterprise data systems
• Apply statistical analysis and basic machine learning techniques to support distribution load forecasting and planning
• Develop and maintain data-driven solutions for distribution system analysis, including data processing pipelines, analytical and simulation models, and visualization or decision-support tools
• Design and implement analytical tools, scripts, and workflows (Python- and/or SQL-based) to improve efficiency, automation, and reproducibility of studies
• Analyze historical distribution system data (e.g., AMI, SCADA, DER, EV data) to identify trends, anomalies, and planning insights
• Support the development of data standards, model validation processes, and integration between engineering tools and enterprise data systems
• Apply statistical analysis and basic machine learning techniques to support distribution load forecasting and planning
• Participate in multi-disciplinary teams to gather input, address comments, and deliver coordinated study results
• Take responsibility for the timely completion of assigned projects while meeting quality, scope, and budget objectives
• Perform technical reviews of studies completed by other engineers and provide constructive feedback to ensure high-quality deliverables
• Mentor and collaborate with team members while contributing to a positive and solutions-oriented work environment
• Perform other related duties as assigned

Requirements:

• Bachelor of Science in Electrical Engineering
• Minimum 4+ years of experience related to distribution utilities/power systems (i.e., electric cooperatives, municipalities, investor-owned utilities, research labs, etc.)
• Strong technical skills and understanding related to utility distribution systems
• Distribution modeling software experience in at least one software platform (CYME, Synergi Electric, openDSS, etc.)
• Strong problem-solving and analytical skills, with the ability to translate power system engineering problems into data-driven solutions, including data processing, statistical analysis, and model development
• Experience in distribution system data analysis, including SCADA data, DER data, EV data, and AMI data
• Familiarity with handling large datasets, experience with actual distribution system measurements (e.g., EV, AMI, SCADA) quality control, and developing reproducible analysis workflows
• Familiarity with statistical analysis and basic machine learning techniques applied to distribution load forecasting
• Experience in automation/programing (Python and/or SQL preferred)
• Proven team player skilled in mentoring and building strong internal and external relationships
• Strong organizational and communication skills, both written and verbal, particularly with respect to explaining technical matters
• Strong interpersonal, problem solving, and analytical skills
• Capable of managing multiple tasks
• Flexible with the ability to manage change
• Have high standards and pride in producing quality reports and products
• Strong technical report writing skills
• Master of Science or higher