Ghost in the data

I was a kid when I first watched Bruce Lee, soon after and my friend signed up for kung fu lessons.

I remember the first time I sat down properly with the Step Functions architecture our team inherited.

In Code Complete, Steve McConnell writes: Software testing alone has limited effectiveness — the average defect detection rate is only 25 percent for unit testing, 35 percent for function testing, and 45 percent for integration testing.

I worked alongside a data engineer who was, by every formal measure, the best performer on the team.

When I started a new role, one of the first things I did was try to understand how data moved through the system.

Some days I open my laptop and by 5pm I genuinely cannot tell you what I did.

Another week, another skills repo on the GitHub trending page.

The Restaurant That Refused to Take Bookings Online Let me tell you a story about a restaurant owner who became obsessed with human connection.

The best SQL doesn’t need comments.

There’s a specific kind of silence in data engineering that I’ve learned to fear.

There’s a particular kind of data problem that doesn’t announce itself.

You watch a conference talk about implementing data contracts, and nobody mentions that the advice assumes you have multiple teams producing data — which you don’t.

Let me tell you about the moment I stopped treating cloud costs as someone else’s problem.

Let me tell you about a graph that changed how I think about data engineering.

Let me tell you about Marcus.

In [Part I], I made the case that your legacy data model isn’t the disaster it looks like.

Let me tell you about a junior engineer called Sam.

There’s a table in a rented house in Queenscliff — nothing fancy, just whatever furniture came with the place — with a hand-drawn map spread across it, dice scattered at the edges, and snacks slowly migrating toward the centre of the board.

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