SkillsEngine - Curate
●
Reduced updated skills data delivery time by up to 84%
●
Delivered a scalable internal solution that supported future growth
●
Replaced inefficient, external workflows that were draining product resources
●
Empowered the curation team to independently manage and edit complex data, reducing dependencies on engineering
Before: Editing in Excel
After: Editing in Curate
Editing skills: before and after Curate.
Role
Lead Product Designer
duration
March 2022 - July 2022
(MVP Launch)
2022 - 2024
(Additional Features)
What I Worked On
Product Design
Product Strategy
User Research
Usability Testing
team
3 Engineers
Director of Engineering
Director of Design
SkillsEngine is a data management platform and tool that lets users create skill profiles utilizing AI and an expertly-curated database of over 35,000 unique skills.
Once built, these skill profiles can be used by employers, job seekers, and educational institutions for credential validation, curriculum alignment, job analysis, and other workforce planning. These skills are regularly updated and maintained by an expert curation team of two Industrial Occupational Psychologists.
the problem
SkillsEngine’s biggest value to users is its ability to provide well-curated skills data but the workflows for editing and maintaining that data were restrictive, inefficient, and costly.
Every content update required our two expert curators to manually edit and manage the skills data using excel spreadsheets. This process could take anywhere from a few weeks to over three months depending on the size of the skills batch being worked on.
Once edits were finalized by the curation team, these large excel files with ten thousand plus rows of skills data would be handed off to engineering to initiate a manual batch import to our database. This was a lengthy and resource-draining process that could sometimes take the backend systems down for an extended period of time.
As the platform continued to grow, it became clear to our team that this workflow was unsustainable. This emphasized the need for a self-editing functionality to help streamline future curation work.
design approach & key decisions
With scalability in mind, we aimed to create a platform that would allow our expert curators to make quick edits and self-publish skills directly.
I was tasked with gathering additional feature and process requirements from the curation team to ensure the functionality met their needs. Through multiple user interviews, I translated their key editing tasks into a simplified, ideal user flow that minimized friction points and made all relevant context easily accessible in one place.
This meant that for any given skill, users should be able to:
1. Locate it quickly through filtering and search
2. View and edit all skill attributes and relevant meta data
3. See all notes or history of skill edits
4. Take actions on it without switching contexts (Save, Publish, Delete, etc.)
This flow became the foundation for our feature set and site architecture. It helped us define which views we needed (landing, search, skill edit, etc.) and what supporting features were essential for MVP launch. Our main goal for this project was to eliminate the need for manual importing, reducing the engineering burden while supporting faster and more frequent skill library updates.
Using the ideal user journey to define and map out features.
navigating constraints & challenges
One of the biggest design challenges was balancing the need for complex functionality for power users while also ensuring easy usability for non-technical users.
Originally our power users wanted a UI where skills were easily accessible and designed to be editable inline from a list view, but early stakeholder feedback indicated that the screens felt too data-dense. Bulk action, commenting, and other secondary features were also removed from the MVP requirements due to increased engineering complexity.
Design decisions put to the test
Early feedback from experts and internal teams guided key UI improvements and helped us prioritize what mattered most
We continued to conduct multiple usability tests throughout the different design iterations. This helped us uncover invaluable insights that brought us closer to the desired MVP platform. After 13 rounds of changes, we successfully launched the first version of Curate.
Video walkthrough of the new curation tool for editing skills.
outcomes and the future of curate
Up to 84% reduction in turn around time for skill updates and the elimination of manual data imports.
After four months of iterating and testing, the MVP launch of Curate empowered the curation team to directly edit and publish skills to the database, cutting content delivery and update time from months and weeks to be instantaneous.
Engineering was freed from managing large batch imports, allowing more focus on strategic development. In the following months post-launch, I continued enhancing Curate by adding features beyond the core editing workflow including pages for editing Skill Profiles and Skill Sets.
Curate edit skills figma prototype.
Curate addressed the immediate need for efficient data management and laid the foundation for scaling the platform to support enterprise users managing their own skill libraries and taxonomies.
This project reinforced the importance of balancing complex functionality with simplicity, especially for a range of users. Iterating quickly and integrating user feedback early on were key to refining the design and ensuring we met both business and user needs effectively.
Made with ❤️ and lots of ☕
© Maria Situ 2025
