Where the Clean Energy Jobs Are

Turning a dense national jobs dataset into an accessible, responsive guide for people exploring careers in clean energy.

A career guide buried in 23 spreadsheets

Fast Company’s annual jobs report turned to the fast-growing clean-energy sector. The audience was job seekers, but the research lived in 23 spreadsheets covering industries, roles, regions, education, and salaries. The job was to turn it into a guide people could absorb quickly and explore on their own terms.

The design problem

Many separate datasets had to become one coherent story.

Readers needed a path from the big picture to practical questions about location, salary, education, and employers.

Detailed comparisons had to stay legible on desktop, tablet, and mobile.

Guide first, then explore

Answer the headline question first: where are clean-energy jobs growing? Then introduce salary, education, and roles one step at a time, so readers move from curiosity to comparison without facing the whole dataset at once.

Finding the structure in the data

I started by finding the information architecture inside the spreadsheets. Only once the data was grouped into clear themes did each section get its visual and interactive treatment.

The result is a web-native system of custom charts, interactive comparisons, and responsive story modules. Visual variety keeps each topic distinct, while one interface language makes the whole feature feel like a single product.

Outcome

From 23 spreadsheets, 74,717 Google Jobs listings became 26,624 clean, categorized jobs in one navigable guide. The editorial team praised how it made an extremely complex dataset feel simple, engaging, and easy to navigate.

Client

Fast Company

Role

Senior Designer (freelance)

Timeline

Sep – Dec 2024

Collaborators

Fast Company editors, print designer, 3D artists, illustrators

What I did
  • Information architecture
  • Data visualization
  • Interactive storytelling
  • Responsive web design
  • UI design
  • Editorial design

From spreadsheets to a story

Twenty-three spreadsheets of raw job data, mapped into a wireframe, then built into one navigable, responsive guide.

Before: the raw research as stacked Google Sheets, from top states for jobs to energy by geography and job type Wireframe: low-fidelity layout of the feature, from the hero and six-chapter menu to the map, salary, education and experience modules
After: the finished site on screen, cycling through the Geography, Salary and Education sections
Geography, intro and Who's Hiring sections of the finished site on desktop

Structure before styling

The data was sorted into clear themes first; each theme then got its own chart and interaction.

Bubble chart, salary ranges and the Job Types carousel, each theme with its own chart

Answer the big question first

Readers start with where the jobs are, then click through job types to see the top states for each.

Print vs. interactive

The report also ran in print. A print designer laid out the pages while I led the digital version, and we compared every chart side by side. A printed spread can hold dense tables, but that much information on one screen is hard to read. So rather than squeeze it all in, the interactive version uses filters, step-by-step reveals and mobile-first layouts, letting readers explore the data around their own questions.

Print: a magazine spread packing the Experience bubble chart, the Salary dot plot, long-form text and an illustration onto one page

Built for every screen

Each chart was redesigned for mobile so detailed comparisons stay readable, not just smaller.

Mobile: the same state map with a job type dropdown, showing Sales
Total Jobs by Energy Type bubble chart on a phone held in one hand Education Comparison for Energy Sectors on a tablet, showing degree levels for Development Engineering and Systems Design across eight energy types

Complex data, made explorable

From 23 spreadsheets, 74,717 Google Jobs listings became 26,624 clean, categorized jobs in one navigable guide. The editorial team praised how it made an extremely complex dataset feel simple, engaging, and easy to navigate.

23
spreadsheets unified
74K+
listings processed
26K+
jobs synthesized