AI Data Engineer

Overview

As one of the first engineers on PowerPlan’s Applied AI team, you’ll build the data foundation behind the AI solutions our own teams use every week, across finance, sales, professional services, and product. Most of the work is finding, cleaning, and defining the data each build needs, then picking the simplest structure that will hold it, and pairing with the team’s AI engineer to put larger solutions into the business’s hands.

PowerPlan builds the financial software behind the companies that keep the lights on, and nine in ten U.S. investor-owned utilities use our platform. The Applied AI team sits inside Strategic Initiatives, works closely with the executive leadership team, and brings that same standard of getting the numbers right to how the company itself runs. The standards you help set early will shape how every build after yours gets done.

Responsibilities

Success will be measured by whether the AI solutions you build data for are in weekly use and run by the business, and by whether new builds start from trusted, shared data instead of fresh exports.

• Learn how the company runs through its data in your first 30 days, deliver an owner-checked first catalog of critical data by the end of your first quarter, and keep it current enough by month 12 that business and technology leaders plan AI work from it.
• Help set the team’s standards for data, connections, and code review from your first 30 days, including how AI tools connect to business systems: read-only by default, no more complex than the job requires, and reviewed by IT and security.
• Pair with the team’s AI engineer on a first build in your first quarter, lead the data on the first larger build into pilot by six months, and by month 12 deliver the data behind at least two larger AI solutions in weekly use and run by the business.
• Agree on the first shared data sets in your first quarter, publish the first one by six months, and have at least two shared, governed data sets in use by more than one team or AI solution by month 12.
• Within your first 12 months, retire hand-built recurring reports by defining the numbers once, so an AI tool can draft the commentary, answer questions, and flag what needs a person’s attention.

Qualifications

• You have two to four years of professional experience as a data engineer, analytics engineer, or in a similar role where writing code to clean and model data was central to the job, or a master’s degree in a related field and at least one year of that experience.
• You’ve turned messy, real data from a business system, a spreadsheet, or a set of documents into something people or an AI tool used, and you can walk us through what broke and how you fixed it.
• Before you build on a number, you trace it through the systems and processes that produce it and find out from the people who own it what it means, and you can tell us about a time a business owner’s explanation changed what you built.
• Agentic coding tools such as Claude Code, Codex, Cursor, or OpenCode are your default way of working, and you know how to plan the work, direct the tool, and check what it produces. The team builds with Claude Code, and we provide the tools.
• You write working Python and SQL and can read and change code someone else wrote.
• You’ve pulled data from an API end to end, including authentication, secrets, paging, and errors.
• You work in Git by habit, treat data access and documentation as part of the build, and write notes a business owner can follow.
• You hold a bachelor’s degree in computer science, data science, statistics, mathematics, information systems, or a closely related quantitative field; a business analytics or other quantitative business degree also qualifies if it included substantial programming coursework.
• You can work from Atlanta in the office at least three days a week and are authorized to work in the United States (this role is not eligible for visa sponsorship, now or in the future).

Even Better If…

• You’ve built an MCP server, an agent skill, or a connector someone else used.
• You have experience with a modern data platform, retrieval over documents (RAG), or data quality checks.
• You’ve worked with CRM, finance, or project data, ideally in or alongside finance, professional services, sales operations, or support.
• You’ve applied continuous improvement methods, such as Lean, Six Sigma, or value stream mapping.
• You hold a master’s degree in a related field, such as computer science, information systems, data science, or business analytics.

PowerPlan is an EOE

Applicant Privacy Notice

Please note that this is a hybrid role that involves a combination of onsite work from our corporate office as well as work from home. While we strive to accommodate flexible working arrangements when sensible, there will be times when onsite work is required. This could include scheduled office days, team meetings, client meetings, or special events.