FP&A Business Intelligence Intern – Summer 2026 at Madison Energy Infrastructure

Tysons, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Jun, 26

Salary

40.0

Posted On

07 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Modeling, Business Intelligence, Data Analytics, Financial Analysis, Excel, Data Ingestion, Data Validation, Reporting Workflows, AI Tools, LLM-based Tools, Forecasting, Project Finance, Data Visualization, Portfolio Performance

Industry

Renewable Energy Semiconductor Manufacturing

Description

Overview Madison Energy Infrastructure (“MEI”) believes in the power of clean energy infrastructure and has quickly emerged as a preeminent developer, investor, asset owner, and operator of distributed generation. This role represents a critical next step in MEI’s evolution toward offering direct, end-to-end services to Fortune 500 corporates, public entities, nonprofits, and other private customers alike. As the company scales, data and analytics are increasingly central to how we monitor financial performance, make investment decisions, and communicate insights across the business. This role sits at the intersection of data analytics, business intelligence, and finance. As the Summer 2026 FP&A Business Intelligence Intern you will work closely with the Finance and Digital teams to help structure data in Snowflake, develop analytical tools, and experiment with emerging AI-enabled workflows that improve how we analyze and visualize portfolio performance. This is an opportunity to gain hands-on experience applying modern data tools, SQL, Python, and AI-assisted development to real financial and operational datasets in a fast-growing infrastructure platform. What You’ll Work On Assist with building data models and analytics tables in Snowflake using SQL to organize operational and financial data into structured datasets for analysis and reporting Support the creation of business intelligence dashboards and reporting tools that provide visibility into portfolio performance, cash flow, and key operating metrics Use Python and SQL to help automate data ingestion, validation, and reporting workflows, improving data quality and reducing manual processes Experiment with AI tools (e.g., Claude Code and other LLM-based tools) to prototype internal analytics workflows, automate analysis, and identify opportunities to improve business intelligence capabilities Work with FP&A and operations teams to translate operational data into financial insights and support Excel-based forecasting, reporting, and project finance analysis What we’re looking for Currently pursuing a graduate degree preferred (e.g., data science, computer science, engineering, economics, finance, or a related field); strong undergraduate candidates will also be considered Comfortable working with data using SQL and Python, with interest in building analytical workflows and data models Strong experience with Excel-based financial analysis and a keen interest in how operational data connects to financial performance; prior coursework or experience in finance, accounting, or financial modeling is a plus Curious about applying AI tools (e.g., Claude Code or other LLM-powered tools) to automate analysis and improve business intelligence workflows Detail-oriented, intellectually curious, and excited to work with real-world financial and operational data (structured and unstructured) in a collaborative environment Location & Schedule: This is a full-time (40 hours per week), hybrid internship based in our Tysons, VA Office. Interns will work four days per week in-office and one day remotely to maximize in-person collaboration and exposure to the business. The 10-week program runs from June 1 through August 7, 2026 with the ability to begin earlier on a part-time basis. Interns will participate in our all-company offsite on June 24, 2026 as part of their immersive experience. The office will be closed in observance of Juneteenth (June 19, 2026) and Independence Day (July 3, 2026). Commitment & Compensation: This is a paid internship. The hourly pay range for this role is $20–$40. Compensation within this range is determined based on factors including academic level (undergraduate vs. graduate), year in program, and relevant experience. To Apply: To apply, please submit your resume through our careers page. Applications will be reviewed on a rolling basis. Selected candidates will be contacted regarding next steps in the interview process. How We Work At Madison Energy Infrastructure, we believe in the power of clean energy infrastructure to drive real impact—for our customers, our partners, and the communities we serve. We’ve quickly emerged as a preeminent developer, investor, and operator of distributed generation, helping organizations across sectors meet their energy goals with certainty, speed, and trust. Our robust portfolio consists of over half a gigawatt of clean energy infrastructure projects across more than 25 states. We’re building a team that thrives on ownership and ambition. As we expand into direct, end-to-end services for Fortune 500 companies, public entities, and nonprofits alike, we rely on collaborative thinkers who bring structure to complexity, energy to execution, and curiosity to every challenge. Our environment is fast-paced and outcome-oriented—but grounded in the belief that how we work together matters as much as what we deliver. If you’re excited to shape the future of clean energy and be part of a high-performance, high-integrity team, we’d love to meet you. Madison Energy Infrastructure is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

Responsibilities

The intern will assist in building data models and analytical tables in Snowflake using SQL, and support the creation of business intelligence dashboards to track portfolio performance and key metrics. They will also use Python and SQL to automate data workflows and experiment with AI tools for analysis prototyping.