Eight Seconds of Silence

Three rounds. A startup. Staff data engineer. Twenty-four hours to prepare.

I walked out today not knowing if I got it. Spoiler: I didn't. And I got almost no feedback - just the quiet that follows a decision that's already been made. It seemed like things were going well from where I was standing. But somewhere in the middle of it, I had a full stop - a complete loss of my train of thought for about eight seconds.

Eight seconds doesn't sound like much. In an interview room, it's an eternity.

The Part Nobody Admits

I've been around data engineering long enough to have lived through Hadoop hype, the Spark era, the great cloud migration, and whatever this AI moment is we're all currently inside. I've seen buzzwords come and go. I've watched job titles get invented and discarded.

And still, every few years, the feeling is the same: like you're starting over.

The technical bar keeps moving. Interview formats evolve. The tools stack up. I had 24 hours to prepare for this one - not ideal - and the sleep deficit showed up at exactly the wrong moment.

What's harder to say out loud is that staying relevant in IT as you age takes genuine, sustained effort. Not because the fundamentals change (they don't, not really - data quality matters whether it's 2005 or 2026), but because the surface area keeps expanding. There's always a new framework you haven't touched yet. Always a concept the interviewers assume you already know.

The Pull Toward the Work

Here's something I keep noticing the further I move up: I want to get back to the hands-on work.

Every step up the ladder pulls you toward strategy, slide decks, and stakeholder management. Useful things, sure. But there's a clarity that comes from being deep in a pipeline, actually building something - debugging a dbt model at 11pm, tracing a data quality issue back to its source - that's hard to replicate anywhere else.

I think that pull is worth listening to. Especially now, when AI is vacuuming up a lot of the surface-level data work. The practitioners who stay close to the actual data - who understand what's happening underneath the dashboard - are going to matter more, not less. The abstraction layers are getting thicker. The people who can cut through them are valuable.

Keep Going

If you're somewhere similar - grinding through interviews, feeling the gap between where you are and where you want to be, maybe questioning whether it's worth it - here's what I'd tell you:

Keep tinkering. Not as a strategy, but as a habit. Stay close to the actual work. Build things, break things, understand things. That compounding curiosity is the thing that survives every hype cycle.

And don't let one setback define the trajectory. Or eight seconds of silence. The data field is long. The career is longer. Stay in it.