Risk Data Lake - White Label Databricks

Risk Data Lake – White Label Databricks

Overview

As the sole UX Designer, I led the design and white-labeling effort for Risk Data Lake, Moody’s customized implementation of Databricks. While Databricks powered the core functionality, the objective was to deliver a branded, intuitive experience aligned with Moody’s product suite—enhancing usability, maintaining visual consistency, and reinforcing product identity within the Intelligent Risk Platform ecosystem.

As the only designer on the project, I owned the end-to-end UX and visual design responsibilities, including:

Conducting a comprehensive UI/UX audit of the native Databricks platform to identify branding and experience gaps

Identifying customization opportunities within Databricks’ OEM partner constraints

Creating a mini design system compatible with both Moody’s and Databricks’ styling frameworks—ensuring visual consistency, usability, and scalability

Designing and implementing branded elements such as login screens, headers, color schemes, welcome messaging, and iconography

Developing visual prototypes and documentation to align stakeholders and support engineering implementation

Collaborating with engineers, product managers, and compliance/legal teams to ensure feasibility, brand integrity, and OEM guideline compliance

Leading internal reviews and iterating based on feedback to fine-tune the user experience and visual language

My Role

Our Solution

The goal was to seamlessly integrate Risk Data Lake into Moody’s product suite while respecting third-party platform constraints. The solution focused on:

Custom Branding Integration

Replaced default Databricks visuals with Moody’s branding (logos, colors, typography)
Customized login screens, headers, and workspace visuals

Tailored Messaging & UI Copy

Introduced custom welcome language and instructional copy to orient users within the Moody’s context
Updated interface text to match Moody’s product conventions

Visual Consistency Across Platform

Ensured the white-labeled experience aligned visually with other Moody’s products
Made subtle layout adjustments to maintain consistency in visual hierarchy and structure

Impact

The final branded experience delivered meaningful results:

Clear Brand Recognition – Users immediately recognized the Risk Data Lake as part of Moody’s platform
Improved User Trust – Familiar branding enhanced user confidence in a complex, data-heavy environment
Stronger Ecosystem Alignment – The Risk Data Lake felt like a cohesive extension of the broader Intelligent Risk Platform
Compliance Success – All customizations adhered to Databricks’ OEM partnership requirements

Challenges included:

Limited ability to restructure the underlying UI framework
Maintaining brand presence without interrupting native Databricks workflows
Balancing stakeholder expectations with technical constraints

Despite these challenges, the project was a success—delivering a polished, on-brand experience that met user expectations and strengthened Moody’s product ecosystem.

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