Data engineering
How do we build pipelines that keep working?
Data engineering turns loose actions into a process that runs: pipelines, integrations and monitoring, with documentation as standard. Data moved by hand goes wrong eventually. The point is that it keeps working, even once the person who built it has moved on.
When do you need this?
Data moved by hand goes wrong eventually. Data engineering turns loose actions into a process that runs, even once the person who built it has moved on.
- Scalable pipelines and platforms
- Monitoring, so you notice before your users do
- Documentation as standard
What happens if this is left alone
- Data comes from four systems that do not know each other, and the joining happens by hand: every single time.
- A process that breaks overnight is noticed at eleven the next morning, when somebody spots a wrong number.
- Scaling up is impossible: what works at a thousand rows stalls at a million, and then it has to be rebuilt anyway.
Through which route do we deliver this?
The same field runs through different routes. Which one fits depends on the scope and duration of what is on the table.
Frequently asked questions
When do you need data engineering?
As soon as the same files are merged by hand, or a dashboard stalls because one source changed. Also when a new source has to be unlocked structurally.
What is the difference between a data engineer and a data analyst?
A data engineer builds the pipelines and platforms the numbers come from. A data analyst turns those numbers into a decision. Putting both in one vacancy means looking for two people at once.
How do you keep it maintainable?
Monitoring on the pipelines, so you notice a failure before your users do. And documentation while building, not afterwards, because documentation afterwards never arrives.
Do you work in our own environment?
Yes. We build in the environment you already have and leave scripts and documentation with you. No dependency on a system of ours is created.
Are you a professional working in this field? Then have a look at the roles we fill and our vacancies.
Looking for someone for data engineering?
Tell us what is on the table. Within two working days you know whether we have someone and what it costs.