From backend engineer to acting CTO in under two years

Overview

The partner joined as a backend developer and left as solutions architect and acting CTO, leading the engineering team that built commerce intelligence over marketplace data at scale. He also led the migration of the complete platform from AWS to on-prem infrastructure, reducing infrastructure costs by roughly 90% while preserving performance and operational control. The product is marketplace intelligence: turning the sprawl of commerce marketplace data into something a sales or strategy team can actually act on.

The business context

Marketplace data is enormous, messy and constantly moving. Sellers appear and vanish, listings change hourly, and the same entity shows up under different names across sources. The engineering problem is not storage. It is resolving all of that into entities a customer will trust enough to pick up a phone and act on.

Get it right and you can tell a business development team which sellers are worth calling, what they sell, roughly what they turn over, and who to ask for. Get it wrong and you have an expensive database nobody believes.

Key decisions

Architect for the shape of the data, not the demo.

Designing and implementing scalable software over large, continuously changing datasets, with the ingestion, resolution and serving paths treated as one system rather than three teams’ problems.

Integrate with what already exists.

Leading the architecture of complex systems while ensuring they fit the existing infrastructure, rather than requiring a rewrite around every new capability. This included migrating the full platform from AWS to on-prem infrastructure, delivering a significant reduction in cloud spend without compromising reliability or delivery pace.

Translate business goals into technical ones.

Working across functions to turn commercial requirements into architecture, and leading the engineering team through delivering it.

What shipped

A seller intelligence product that lets a commercial team filter a marketplace by seller type and revenue tier, see revenue, top products and volumes before a first conversation, and reach a verified contact.

• Robust, scalable APIs over large scale marketplace data.
• System architecture and integration across an existing platform.
• Technical leadership of the engineering team and its delivery.
• Backend systems tuned for query performance at data platform scale.