Context
DataHub was the central platform responsible for enabling data ingestion across a complex marketplace ecosystem. As platform adoption increased, the team became responsible for onboarding new ingestion requests, configuring data flows, and supporting internal stakeholders throughout the process. While the platform delivered significant business value, the operating model created a growing dependency on a single team, making it difficult to scale efficiently.
The Challenge
Over time, the DataHub team became a bottleneck for internal stakeholders. Every new ingestion request required manual intervention, creating a growing backlog, long delivery lead times, high levels of repetitive operational work, limited team scalability, and strong dependency on the DataHub team. Rather than focusing on optimizing the queue itself, we stepped back to understand the root cause. The real challenge was not the backlog. It was the operating model that required every ingestion request to pass through the same team.
My Role
- Leading discovery with business stakeholders and engineering teams
- Understanding recurring ingestion patterns across different business units
- Defining the product vision and long-term roadmap
- Identifying opportunities to reduce operational dependency
- Aligning stakeholders around a scalable platform strategy
- Driving delivery together with multiple engineering teams
Product Approach
Instead of continuing to process ingestion requests individually, we redefined the problem and introduced Ingestion as a Service within DataHub. The goal was to transform DataHub from a request-based service into a self-service platform capability. Key principles included self-service onboarding and configuration, standardized ingestion workflows, reusable platform capabilities, reduced manual intervention, and greater ownership for internal teams. The result was a platform experience that enabled teams to configure and manage ingestion flows more independently while maintaining governance, consistency, and scalability.
Outcome
The initiative transformed both the platform and the way the team operated. DataHub evolved from a reactive service organization handling individual requests into a scalable product capability supporting multiple teams simultaneously. Target onboarding time was reduced from 32 days to 1–2 days, repetitive operational work decreased, internal teams gained autonomy, and engineering capacity became available for strategic initiatives.
Measures of Success
- 32 → 1–2 days target onboarding time
- Reduced manual request handling
- Reduced operational overhead
- Increased self-service adoption
- Faster launch of new ingestion flows
- Increased strategic engineering capacity
The Transformation
DataHub was much more than a technical platform initiative. It represented a shift in the team's operating model. Instead of acting as a reactive bottleneck responsible for handling individual requests, the team became the owner of a scalable product capability that empowered multiple stakeholders. The most important transformation was not technological. It was moving from a service mindset to a product mindset.
What I Learned
One of the biggest lessons from this initiative was that scaling is often achieved by redesigning ownership rather than adding more capacity. By focusing on the underlying dependency model instead of the symptoms, we were able to remove bottlenecks, empower stakeholders, and create a platform that could grow without requiring proportional growth in the team. The real breakthrough was not building a better process. It was building a better operating model.