You bring in a consulting firm to help with data. They show up with a clean pitch deck, talk about modern architecture, and make big promises. A few weeks later, your team is still waiting for working pipelines. Your dashboards are incomplete. Your engineers are doing cleanup instead of building.
It happens more often than people admit.

A Good Pitch Doesn’t Mean Good Execution

Some partners know how to talk strategy. Fewer know how to build systems that work in production.
I once worked with a vendor who hardcoded business logic into a Spark job. No tests. No docs. No visibility. When requirements changed, we spent weeks trying to figure out where to make the edits. That one shortcut caused delays across three teams.
The issue wasn’t tools or frameworks. It was the lack of care in execution.

What Poor Delivery Really Costs

The impact of a weak data partner goes far beyond late projects.
You lose trust across teams.
Leaders make decisions based on outdated data.
Data engineers burn out fixing someone else’s mistakes.
Business users stop relying on reports altogether.

While your company is cleaning up broken pipelines, your competitors are making faster decisions and gaining ground.

What to Watch Out For

Here are some warning signs I’ve seen in the field:
Endless planning meetings with no delivery
Every challenge leads to a new tool suggestion
No focus on reliability, testing, or monitoring
Junior developers placed on complex tasks without support
Poor communication once the project is live

If any of these sound familiar, it may be time to reconsider who you’re working with.

What the Right Partner Does Differently

A strong data engineering partner will:
Ask about your goals, not just your systems
Build pipelines that are easy to change and monitor
Explain their work clearly and document everything
Share knowledge with your team instead of keeping it to themselves
Stick around when things go wrong and help fix them

They will not disappear after the final invoice. They will treat your success as their own.

A Final Thought

Good data engineering is not about buzzwords or trendy tools. It is about building systems that support your business and grow with your needs.
If your team is spending more time fixing pipelines than using data, take a step back. Look closely at the people helping you build. A reliable partner makes everything smoother. A careless one can set you back for months.