The Unglamorous Work That Keeps a Product Moving: Our Engagement with EY
Not every engagement is a dramatic transformation. EY needed a reliable engineering team to keep a data platform module healthy and ensure product decisions were grounded in data they could actually trust.
Sprint-cadence
Feature delivery rhythm
Zero
Data trust incidents post-engagement
Continuous
Debt reduction (not deferred)
100%
Roadmap visibility for product team
The challenge
EY were building out a module within a large internal data platform — a system designed to give product and business teams the visibility they needed to make informed decisions. The platform was already in motion; there was no crisis to solve. What they needed was consistent, disciplined engineering to keep the module healthy and ensure the data flowing through it was trustworthy enough to act on. Products built to surface data often accumulate subtle reliability problems: fields that go stale, edge cases that skew aggregates, bugs that only surface at scale. Left unaddressed, these erode trust in the data itself, and product teams start working around the platform rather than with it.
What we did
- 1
Full module ownership
We took end-to-end responsibility for the module — maintenance, bug fixes, and new feature development — so the product team had a single accountable engineering partner rather than tickets disappearing into a backlog.
- 2
Sprint-by-sprint product dialogue
Every sprint started with one question: what decisions are you trying to make, and what data is missing or wrong? This kept engineering work anchored to real product needs rather than a disconnected roadmap of technical tasks.
- 3
Root-cause discipline on every bug
We treated each bug not as something to close, but as a signal about the system. Most reliability problems in data platforms are symptomatic — fixing the surface without understanding the cause means the same class of bug resurfaces in a different field six weeks later.
- 4
Proactive debt reduction
Rather than deferring complexity to a future rewrite, we addressed technical debt continuously — small increments, every sprint. This kept the codebase from calcifying and meant the team could keep adding features without each new one becoming harder than the last.
The outcome
- Product teams had a module they could rely on — data was accurate, timely, and structured for decision-making, not just reporting.
- Technical debt was addressed continuously rather than deferred until a forced rewrite.
- Product roadmap velocity improved as the team stopped fire-fighting data reliability issues mid-sprint.
- A working engineering partnership where product and engineering trusted each other enough to move faster.
Stack & approach
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