In the next in his series about demystifying data engineering, Claudio Diniz interviews Will Faithfull and learns that if you have an interest or curiosity in the data domain and analytics side of things, even if you know next to nothing about them already, that will stand you in great stead. 95% of the skills will be second nature to you, so you only have to focus on that remaining 5%.

In the next in his series about demystifying data engineering, Claudio Diniz interviews David Pardoe and learns why it is absolutely key to have an in-depth understanding of data, and not just the code that manipulates it. Learn more here:

In his latest series on how to move from software engineering into data engineering, Claudio Diniz interviews Lewis Crawford who aptly explains, among other things, how at some point scale catches everyone out, and therefore how important it is to consider on large projects:

How finding hidden data products can greatly empower capabilities such as Machine Learning within an organisation

In the next in his series about demystifying data engineering, Claudio Diniz covers, among other things, the skills a data engineer must have that a software engineer usually won’t.

How Scott Cutts accidentally transferred from being a software engineer to a data engineer, and experiences of being in data engineering.

What exactly is a data engineer? Demystifying data engineering to encourage more software engineers to become one.

Learn why we advocate that data oriented projects should always use the well-known software engineering best practices. This article shows how you can apply TDD using the emerging dbt data transformation tool.

Two tools to create a language agnostic data pipelines architecture that can be easily reused and adapted in multiple cases and for different clients plus a public reference implementation of this architecture