Two massive mistakes that nearly ended my data career
What deleting prod and racking up $8k in AWS taught me about being a real data engineer
Hi fellow data pro, Yordan here,
I didn’t learn these lessons in any course. Nobody teaches you this stuff upfront. They should.
I learned them by breaking things. Important things. Things that, honestly, could’ve gotten me fired if I hadn’t been extremely lucky.
There were two moments in particular that almost ended my data career before it even got going properly. Both of them happened in production. Both of them cost real money. And both of them exposed weaknesses in my technical knowledge, judgment, processes and mindset.
These two moments still shape how I work today.
If you're a data engineer, or planning to become one, I hope this saves you from making the same mistakes I did.
The first time: I wiped production clean
It always starts the same way. A small issue. A simple fix.
I was looking into a minor data inconsistency. Nothing critical. Some transactional data looked off, and I wanted to clean it up quickly before it snowballed into something bigger.
I was tired that day. I probably shouldn’t have even been doing this work at that hour. But you know how it is: "just one more thing before I log off."
So I connected to production.
Yes, production. The actual application production database.
I didn't give it much thought. We didn't have much of a separation between environments. Dev, staging, prod, they were technically different, but the access model was basically wide open for senior engineers.
I wrote my query:
delete from transactions;And I hit execute.
No WHERE clause. No safety check. No second thought.
I still remember staring at the output.
0 rows remaining.
All of it. Gone.
In less than a second, I had deleted every transaction in our system. Every single one. Not a copy. Not a reporting dataset. The core production table. The thing that actually powered the live business.
The instant panic
You know that feeling when you do something irreversible? That sinking, stomach-dropping, cold-sweat kind of panic?
I just froze.
I couldn’t breathe. My fingers hovered above the keyboard. My mind was racing but completely blank at the same time.
It took me a few seconds, seconds that felt like hours, before I called my manager.
He came to my desk, heard my voice, and knew something serious had happened.
I told him exactly what I did. No point hiding it. He was quiet for a moment and then said:
Okay. Don’t touch anything else. Let’s go to the backups.
We kicked off the restore.
We got lucky. Very lucky
Thankfully, we did have backups. We had point-in-time backups running daily. We were able to restore most of the data fairly quickly.
But we still lost an hour of data. Transactions made during that window were gone. There was no way to fully reconstruct them.
The business impact? Not catastrophic, but not nothing either. We had to manually work with support teams, customers, and financial records to patch the gaps as best as we could.
But the emotional impact? That stayed with me much longer.
I kept replaying the moment in my head:
Why didn’t I double-check?
Why didn’t I run it in staging first?
Why didn’t I add a WHERE clause?
How could I have been so careless?
What I learned from breaking production
In hindsight, that moment changed how I view production forever.
I learned a few things right away:
Never give raw access to production lightly. Even senior engineers can, and will, make stupid mistakes.
Backups are not optional. but also: test your restores. Having backups saved us. But if those restores had failed the situation would’ve been a hundred times worse.
Peer review everything. Especially destructive queries. Especially when tired. Especially when "it’s just a quick fix."
But even more than those tactical lessons, I learned that production isn't just another database.
Production is real people. Real customers. Real money. Real businesses depending on the data you’re touching. Every query carries weight.
You can’t approach production like a developer playing in a sandbox. You have to respect it.
Then i made an even more expensive mistake
I wish I could say that after deleting production data, I became the most cautious data engineer on the planet.
I didn’t.
A few yers later, in a different company, I made my second major mistake. And this one cost actual money.
The $8,000 overnight bill
At the time, I was the only data engineer on the team. Which meant most data infrastructure decisions fell on me.
We were running on Redshift. And like every Redshift setup eventually, we started hitting performance issues. Slow queries, backlogged workloads, frustrated stakeholders. I wanted to fix it.
One night, after a long day of debugging, I decided I’d resize the cluster.
Simple enough, right?
I opened a PR to scale up the cluster size. Much larger nodes, just to stabilize things overnight. My plan was to monitor it in the morning, see how it behaved, and scale it back down.
It was late, past midnight, but I figured I could squeeze it in before calling it a night.
The PR got approved quickly on the next morning. Nobody really reviewed it carefully. Honestly, everyone assumed I knew what I was doing.
I mean, I was THE data engineer.
The next night, the cluster resized. Everything looked stable.
I went to bed.
The morning surprise
When I checked the AWS billing console the next morning, my heart dropped.
We had burned through $8,000 in compute costs. Overnight.
To put that in perspective: that was our entire AWS budget for the month. Gone in a few hours.
And all because of a typo in Terraform. What I thought would cost us maybe a few hundred bucks ended up costing exponentially more because I was too sleepy.
The real problem wasn't Redshift
Looking back, this wasn’t really a Redshift problem.
It was a process problem. A culture problem. And ultimately, a me problem.
I was tired.
I was working alone.
Nobody questioned my decision, because I didn’t invite anyone to question it.
That kind of solo ownership mentality is dangerous.
When you're the only person responsible for a system, you stop seeing your blind spots. You start assuming you're always making the right call.
And when you mix that with exhaustion, you create the perfect storm for expensive mistakes.
The big pattern behind both mistakes
Both of these failures came from the same root cause:
I was trying to be the hero.
I didn’t want to bother others late at night.
I wanted to "solve it" before anyone noticed.
I didn’t want to slow things down with extra reviews.
I didn’t want to admit that I wasn’t entirely sure.
That lone-wolf mindset feels productive in the moment. But it’s dangerous.
In production, you don’t need heroes.
You need systems.
Is this resonating with you? I'd greatly appreciate your feedback in the form of a quick testimonial. Submit yours now
How I changed my entire approach
After these two very painful experiences, I completely changed how I approach data engineering work. Especially anything touching production.
I don't allow direct prod access anymore
Nobody, including me, executes queries directly on prod. Everything flows through controlled pipelines, versioned code, and audited processes.
Destructive queries require pre-verified backups
Any operation that deletes, modifies, or rewrites data is paired with a verified restore point. We simulate the rollback before running anything.
Infrastructure changes follow a strict review process
All cluster changes, scaling operations, and infra tweaks go through pull requests, with multiple reviewers. No exceptions. No "it's a small change."
No more late-night changes
If it’s not urgent, it waits. Tired brains break systems. Period.
No-hero culture
We normalized double-checking each other's work. Asking for a second pair of eyes is the default, not the exception.
Juniors start safe
New hires start by working entirely in sandbox environments, where they can break things safely and learn without fear.
What I would tell any data engineer today
If you’re earlier in your career and reading this, here’s what I wish someone had drilled into me:
Your job isn’t to avoid all mistakes. That’s impossible.
Your job is to design systems that absorb mistakes.
If your system depends on you being perfect, you’re building it wrong.
Ask for help. Even when you feel stupid for asking. Especially then.
Because at some point, you’ll be tired. Or distracted. Or stressed. Or in a rush.
And you want systems that protect you from yourself.
Final thoughts
If you’ve broken production before. You’re not broken. You’re not doomed. You’re not the only one.
Every senior engineer I know has their own "I broke prod" story. Some of them just aren’t brave enough to talk about it.
The difference isn’t whether you’ve made mistakes.
The difference is whether you learned from them, and whether you built safety nets afterward.
Apply blameless postmortem incident reports. They are a massive game changer.
I made these mistakes so you don’t have to.
If you take nothing else away from this:
Design your systems assuming you will screw up. Because you will.
That’s not being pessimistic. That’s being realistic.
That mindset will save your company millions and your career many sleepless nights.
If you’ve ever made your own terrifying prod mistake, share it. Make it public. Normalize it. These stories help more people than you realize.
Thanks for reading,
PS: Got value from this post? I'd love to hear your feedback in a quick testimonial. It only takes a minute and truly makes a difference. Write your testimonial.