At some point, I stopped seeing code as logic and started seeing it as pressure relief.
Every function, every pipeline, every table schema — It’s not just solving a problem. It’s releasing pressure that built up somewhere else in the system.
You can feel it if you’ve been in the work long enough.
There’s the pressure of:
A deadline
A legacy report no one understands
A VP who wants “the numbers to match”
A BI team that inherited a warehouse no one owns
A product decision made with no metric definition
A compliance deadline with teeth
And all of that—all of it—gets pushed downstream.
Into code.
Into airflow DAGs.
Into recursive functions.
Into weird conditional joins someone wrote at 11:49 PM.
Most engineers will never admit it, but half the systems we build are emotional regulation mechanisms.
“Make the numbers line up.”
“Get the alerts to stop.”
“Patch this until the reorg happens.”
“I don’t know why that table exists, but we can’t delete it.”
Pressure, coded into permanence.
It’s easy to forget this when you’re knee-deep in YAML or debugging a failing load job. But every piece of the stack has tension baked into it.
Code is rarely a clean artifact of logic. It’s usually a snapshot of a moment when someone needed to make the pressure stop.
🧱 What does this mean for data pipelines?
It means your data pipeline isn’t just about moving facts from A to B. It’s encoding:
Institutional memory no one wrote down
Naming decisions made under time duress
Definitions that were negotiated, not designed
Fear, politics, turnover, denial
It’s not elegant. But it’s honest.
When I read data pipelines now, I don’t just look for flow. I look for tension points:
Why is this join so complex?
Why are we filtering out 0s here? Who got burned by that once?
Why is this pipeline named after a thing we deprecated two years ago?
Every weird edge is a story. Every hardcoded value is a scar. Every undocumented column is a moment of pressure that was never metabolized properly.
📉 Why is this pressure getting harder to manage?
Because every company has become a tech company.
The systems are digital. The data is live. The interfaces are connected. That’s the world now. The world demands it.
But most companies still aren’t led by people who understand tech as a material.
Their leaders are brilliant—finance, strategy, ops, brand. But they weren’t trained to read code like a weather map. They can’t feel when a system is stretched too tight.
So the pressure builds. And builds. Until it bursts into the inbox of someone writing a pipeline they didn’t design, to fix a problem they didn’t cause, with a deadline they didn’t set.
That’s not a bad org. That’s a normal one, in 2025.
⚖️ A final turn: data as pressure
What an organization is actually doing = reality
What we say about what it’s doing = language
What we store about what it’s doing = data
As our world becomes more complex—more integrated, regulated, personalized, and real-time—so do our organizations.
And complexity produces data. And data produces pressure.
We keep storing it. Reporting it. Syncing it. And somewhere, someone has to make it hold together.
Usually, that person writes code.
So what do we do with that?
You stop pretending your pipeline is just infrastructure. You start treating it like biography.
You learn to read it like a system of belief. Because it is.
And maybe—just maybe—you stop judging the mess so harshly.
Because beneath the jank, the hacks, the retries, and the commented-out blocks—
there’s a team that did what they had to do. With the context they had. Under pressure no one upstream wanted to acknowledge - or may even be capable of acknowledging.
This isn’t a call to celebrate duct tape. It’s a call to respect the system as a living artifact of decision pressure.
To see what’s encoded in the code. To trace the pressure lines. To know where the system is ready to break again.
And to build—not with shame—but with context.
So here’s a question:
If you believed this—that data engineering is the practice of metabolizing organizational pressure—
What would you build differently?
Zac
@dealcharts
commandreveal.substack.com
Field Notes on Perception is an new series about how we see—systems, data, patterns, and the invisible structures that shape how we think and build. It’s a personal lens on trust, clarity, and cognition in a noisy world.