Hiring a data engineer is the obvious move when you want to become more data-driven. It feels like the right call: you need infrastructure, you hire an infrastructure person. But the role comes with a real cost, a timeline, and a specific set of problems it solves. This post breaks down what that looks like in practice, and where the math points a different direction.
What a data engineer actually does
Data engineers build and maintain data infrastructure. They set up pipelines, manage data quality, and ensure data flows from A to B.
But here's the thing: moving data doesn't create insights. Data engineers lay the foundation, but they don't directly answer business questions or drive decisions.
It's your data analysts who turn data into insights. They analyze trends, build dashboards, identify opportunities, and help you make better decisions. That's where the real value is.
The true cost of a traditional data setup
Let's break down what a minimal data team typically costs:
Personnel
100,000/year - Senior Data Engineer
80,000/year - Data Analyst
Platform costs
18,000/year - Fivetran (data pipelines)
4,200/year - Cloud Composer (orchestration)
12,000/year - Data warehouse (Bigquery/Redshift)
Total: ~215,000 per year
A better approach: invest in analysts, not infrastructure
What if you could skip the data engineer hire entirely? What if your analysts could start adding value from day one, without waiting for someone to build the foundation first?
That's exactly what Mark Your Data Platform offers.
What you get
- Complete data infrastructure - Cloud-native, scalable, and maintained by us
- Data pipelines - We ingest data from your sources using DLT, an open-source alternative to Fivetran
- Data models - We structure your data using DBT so analysts can query it easily
- Cost-efficient storage - We use MotherDuck instead of expensive data warehouses
- Onboarding support - We help your analysts get started quickly
The math: save up to €100K per year
Traditional approach
100,000 - Data Engineer
35,000 - Platform tools
80,000 - Data Analyst
Mark Your Data Platform
0 - No data engineer needed
~15,000 - Platform subscription
80,000 - Data Analyst
Save ~120,000/year
What about customization?
A common concern: "Won't I lose flexibility without an in-house data engineer?"
Our platform is built on open-source tools (DLT, DBT, MotherDuck) that are fully customizable. Everything is code, stored in Git, and can be modified as your needs evolve.
Because it's all code, tools like Claude can help maintain and extend it. That's something you can't do with SaaS configuration UIs.
Already have a data engineer?
If you've already hired a data engineer, you can still save significantly by switching from expensive enterprise tools to our lightweight stack.
Learn how to save €30K+ per year on platform costs
The bottom line
Data infrastructure is a commodity. Don't overpay for it.
With the Mark Your Data Platform, you get a complete, production-ready data foundation at a fraction of the cost. Your analysts can start adding value immediately, without waiting months for infrastructure to be built.
Invest your budget where it creates real impact: in the people who turn data into insights.