Data Engineering Migrations Are Hard
The brutal truth is that you’re likely to fail at migration projects unless you fix this
Greetings, Data Engineer,
Most data leaders are lying to themselves.
You think your next migration project is going to work. This time will be different.
It won’t.
Because it’s not your cloud platform or your stack that’s broken.
It’s your ability to manage expectations, politics, and people. And unless you fix that, you're already screwed.
Your next data project is destined to die
Most data leaders I talk to are knee-deep in migration hell right now. Some know it. Some are still blissfully in denial. But almost all of them are making the same mistake.
They think their migration project will succeed because they’ve got smart engineers, a detailed JIRA board, and a shiny new cloud provider.
Nope. It’ll fail.
Not because your team is lazy or your tech stack is weak. But because of one brutal reason you don’t want to admit:
You suck at stakeholder management.
And no, I'm not judging. I've been there too.
I’ve led data migrations that felt more like hostage negotiations than tech projects. I've watched my roadmap burn down while execs changed priorities weekly.
I've seen a team build a perfect pipeline… only for no one to use it because we forgot to align with business needs.
So yeah, this piece isn’t going to coddle you.
It’s going to call you out.
But it’ll also show you how to fix it.
Because once you learn how to influence people who have no idea what “ETL latency” means, but still sign your budget, you’ll become unstoppable.
75% of cloud migrations run over budget.
In 2021, McKinsey found something wild: 75% of cloud migrations go over budget.
And here’s what’s even more damning: those migrations don’t just go over budget. They often miss the business case entirely.
After months (or years) of effort, the company ends up with:
Data they don’t trust
Reports they don’t use
A new cloud bill no one understands
And the root cause isn’t technical debt or crappy documentation.
It’s misalignment.
The business expects magic. The data team expects clarity. Neither side gets what they want.
Here’s why data migrations really fail
1. Underestimating the chaos
Every legacy system is a haunted house.
You open one door, and three ghosts fly out: hardcoded business logic, undocumented Excel files, or that one guy who left in 2019 but still owns 60% of your data pipelines.
Most data teams think a migration is a lift-and-shift job.
It’s not. It’s an excavation.
You have to dig deep, unearth tribal knowledge, and map dependencies no one has touched in years. If you skip that step, you’re basically running blind.
You’ll discover the real complexity halfway through the sprint. When it’s too late. When the budget’s tight. When your execs want results.
And that’s when panic sets in.
2. No methodology = no mercy
If your migration plan is a bunch of bullet points in a Notion doc... I’ve got bad news.
You need structure. Methodology. A plan with clear milestones, owners, testing criteria, and rollback procedures.
This isn’t a sexy agile moment. It’s project management warfare.
Yet most teams start migrating before they finish scoping. No clear sign-off. No risk mitigation. No plan B.
Just vibes (No, not these vibes).
And let me be clear, vibes don’t scale.
A real migration plan should include:
Source-to-target mapping
Data quality assessments
Change impact analysis
Rollback contingencies
Stakeholder RACI charts
If your plan doesn’t include these—start over. You're already late.
3. No change management = silent failure
This is the one that stings the most.
You think you did a great job. Data landed in the new system, pipelines run, dashboards look slick.
But no one uses them.
Why?
Because you didn’t bring people along.
Migrations aren’t just about data. They’re about how people access, understand, and act on data. And if you don’t manage that change. Users will stick to their Excel exports and custom hacks.
No amount of Snowflake credits will save you then.
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You need:
Communication plans
Internal champions
Training sessions
Feedback loops
And guess what. That’s stakeholder management too.
Which failure path are you on?
There are dozens of ways a migration dies.
But most failures fall into two buckets:
Project chaos (bad scoping, bad planning)
Stakeholder chaos (no alignment, no buy-in)
And here's the part no one likes to hear:
The stakeholder stuff is your job.
Yes, you, the data leader.
You have to translate technical constraints into business risks.
You have to build relationships with non-technical sponsors.
You have to manage up, across, and down.
And if you don’t, you’ll join the 75% club.
What actually works
Let’s talk redemption.
You want your migration to succeed? You need three things:
Relentless discovery
Interview every stakeholder. Map every dependency. Hunt down shadow data systems. Leave no stone unturned.
Structured planning
Use real project management. Milestones. Gantt charts. Risk registers. Technical documentation. Assume everything will break and plan for it.
Stakeholder alignment
Run working groups. Share roadmaps. Get executive signoff. Update weekly. Communicate risks before they blow up.
And if you're thinking, “That sounds like a full-time job…” you're right.
It is.
That’s why I created the Data Leader’s Influence System. It’s not a technical course. It’s a playbook for becoming the kind of leader who can ship big, ugly, high-risk data projects without burning out or getting steamrolled.
Final thoughts
Migrations are hard.
Not because the tech is hard, but because humans are messy.
If you don’t learn to manage people, politics, and priorities, it doesn’t matter how good your pipeline is.
Your project will still die.
So stop chasing the perfect tool. Stop blaming legacy systems.
Start managing the room.
The real migration strategy is stakeholder strategy
Data leaders fail when they ignore power dynamics.
Technical brilliance means nothing without influence.
Your job isn’t to move data. It’s to move people.
And if you want to lead successful data migrations, start by learning how to speak the language of business, not just SQL.
If that resonates with you, check out my course: Data Leader’s Influence System
Cheers,
PS: If you're tired of watching migrations fail or being blamed for it, learn how to manage stakeholders like a pro.