MEROXA TURBINE
MEROXA TURBINE

Designing data observability for real-time stream reliability

Designing data observability for real-time stream reliability

Leading a strategic product pivot by deeply engaging with users to expand Meroxa’s addressable market into production engineering teams—but that's just the beginning of the story.

Leading a strategic product pivot by deeply engaging with users to expand Meroxa’s addressable market into production engineering teams—but that's just the beginning of the story.

4x
improvement
in engagement
10x
addressable
market
33%
reduction in time
to resource creation

Background

Background

Meroxa is a data service that was built to empower data teams. Originally, the product was low/no-code to further democratize the creation of data pipelines.

Meroxa is a data service that was built to empower data teams. Originally, the product was low/no-code to further democratize the creation of data pipelines.

The scenario

The scenario

Meroxa's initial product vision was hitting a wall. Our low/no-code pipeline builder for Data Engineers had reached an engagement ceiling, and user research was revealing uncomfortable truths: the addressable market was significantly smaller than projected, and our product complexity was misaligned with actual user workflows. The company needed a new direction to achieve venture-scale growth.

Meroxa's initial product vision was hitting a wall. Our low/no-code pipeline builder for Data Engineers had reached an engagement ceiling, and user research was revealing uncomfortable truths: the addressable market was significantly smaller than projected, and our product complexity was misaligned with actual user workflows. The company needed a new direction to achieve venture-scale growth.

My role

Principal Product Designer

Principal Product Designer

Working closely with the VP of Product, who initially discovered the opportunity, I helped develop and push forward the research findings that would ultimately influence the executive decision to pivot our entire product direction.

This collaboration meant taking ownership not just of design, but of market intelligence that would reshape the business.

What we started with

What we started with

Pipeline list

Pipeline builder

Action: Strategic market research

Action: Strategic market research

Through comprehensive user research, I validated and expanded upon the VP of Product's initial discovery that Software Engineers—not Data Engineers—comprised the majority of our user base. This insight revealed a 10x larger addressable market opportunity that completely changed our strategic positioning.

Through comprehensive user research, I validated and expanded upon the VP of Product's initial discovery that Software Engineers—not Data Engineers—comprised the majority of our user base. This insight revealed a 10x larger addressable market opportunity that completely changed our strategic positioning.

Executive influence

Executive influence

Together with the VP of Product, I presented these critical market insights directly to executive leadership, facilitating the strategic pivot decision. This required not just research skills, but the ability to translate user insights into business strategy.

Together with the VP of Product, I presented these critical market insights directly to executive leadership, facilitating the strategic pivot decision. This required not just research skills, but the ability to translate user insights into business strategy.

Product transformation leadership

Product transformation leadership

I championed the evolution from a browser-based pipeline builder to a code-first data application framework (Turbine). This meant redesigning our entire information architecture for developer-centric workflows and evolving our "Yoshi" design system to support rapid prototyping during the transformation.

Additionally, going the direction of code-first provides the capability of making highly complex data applications that are more acyclical than linear singular data pipelines.

I championed the evolution from a browser-based pipeline builder to a code-first data application framework (Turbine). This meant redesigning our entire information architecture for developer-centric workflows and evolving our "Yoshi" design system to support rapid prototyping during the transformation.

Additionally, going the direction of code-first provides the capability of making highly complex data applications that are more acyclical than linear singular data pipelines.

Opportunities

Expand the Yoshi Design System to be more robust

Error detection and troubleshooting capabilities

Where we went

Where we went

Working with internal and external engineers in search of providing the most value as they perform their tasks, we explored their current tooling and requirements.

Logs for troubleshooting.

In order to garner more interest from enterprise customers, I designed multi-environments and mulit-user accounts.

Evolution of the Data App detail

Outcomes

Outcomes

This project was a valuable exercise in developing strategy from ambiguous situations and collaborating across functions to apply research insights that inform key business decisions

This project was a valuable exercise in developing strategy from ambiguous situations and collaborating across functions to apply research insights that inform key business decisions

10x larger addressable market by targeting Software Engineers vs. Data Engineers

4x improvement in user engagement metrics post-pivot

High-value enterprise contracts directly attributed to the strategic repositioning

33% reduction in resource creation time through streamlined developer workflows

Platform evolution from simple pipelines to complex data application development

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