Hybrid Power Systems Data Engineer – Transmission Analytics

Dominion Energy; Glen Allen (VA); Hybrid; USD 90,000 - 150,000; Full time

Benefits offered by this job

Health, dental, vision benefits

401k with matches

Tuition reimbursement

Paid holidays

Job summary

Dominion Energy seeks an Engineer to advance Electric Transmission Operations Analytics. You will bridge real-world grid data with actionable intelligence, building front-end components and time-series models. Expect collaboration across teams to apply data storytelling for improved decision making.

The role emphasizes analysis, development of data-driven insights, and ensuring PI system reliability while supporting a hybrid work schedule and ongoing learning.

Qualifications

• 4-year Engineering degree from ABET-accredited program or equivalent.
• Candidates with international ABET-equivalency are considered.
• Strong ability to translate requirements into front-end designs and data visualizations.
• Experience using programming languages to create data analyses and visualizations.

Responsibilities

• Translate requirements into user-facing components of applications.
• Model time-series and asset data; leverage PI features and APIs to create data services.
• Develop data-driven insights to support grid monitoring and decision making.
• Ensure PI system availability and reliable operations for current and future state.

Skills

Front-end development

Data analysis

Python

C#

R Studio

Advanced Excel

Visual Basic

SQL

ArcGIS

Power systems knowledge

Time series data

Education

ABET-accredited engineering degree

Tools

PI Data Archive

PI SDK

PI AF SDK

PI System Administrator

Visual Studio .NET

Job description

Dominion Energy seeks an Engineer to advance Electric Transmission Operations Analytics. You will bridge real-world grid data with actionable intelligence, building front-end components and time-series models. Expect collaboration across teams to apply data storytelling for improved decision making.

The role emphasizes analysis, development of data-driven insights, and ensuring PI system reliability while supporting a hybrid work schedule and ongoing learning.