[Orou]

I would also vote for "data engineer" (it's my current job title).

You very likely don't want a data scientist to be doing a data engineer's job (and they probably don't want to be doing it themselves!). While there are similarities, data engineering tends to be a lot closer to software development than data science. If you're advertising for a data scientist role, don't expect them to be happy if 80% of their job is writing ETL scripts and cleaning datasets.

I think the reason there has been a flattening in data scientist job growth more recently is that lots of companies hired data scientists to build cool ML applications but had no infrastructure in place to support advanced data analysis. These companies didn't realize they needed to walk before they could run, and that what they really wanted was data analysts and engineers to build the foundation for a strong data science function.

Tools like dbt have been great for advancing an ELT approach to managing data pipelines, where modeling for BI tools, business users, and data scientists alike can all happen in the warehouse and ensure consistency in data usage across the company.

[ramraj07]

The one issue is that the gamut of experience and ability in a data engineer (and the salaries) is extremely wide, far wider than I’ve seen for any other role. Hiring a good DE is so hard!

[dijksterhuis]

Seconded.

I was a bit sad to not see any mention of a data engineer anywhere in the article.

Like, if you gave me access to all the prod tables and the warehouse I'd be having a whale of a time and (hopefully) delivering enough business value to automate some of the more regular "English to SQL" translations.

> You very likely don't want a data scientist to be doing a data engineer's job.

100%. This is one of those things that would make "disgruntled ML people" in the article want to leave.

[rickeydidio]

This is spot on. As someone who has been looking for a data analyst role, I’ve actually read quite a few DS reqs that were geared more towards infrastructure and ETL. Then the flip side with the DE reqs wanting NumPy and Pandas along with the infrastructure and ETL. Weird, right?

[sails]

IMO data engineer roles are further subset into:

1. kafka / streaming oriented software engineering

2. data warehouse and ETL/ELT development for analytics

[dijksterhuis]

A good data engineer understands and can work with both of these.

They're both "data in, data out" mental models that are part of the Lambda architecture which every data engineer should at least know about [0].

But if you want a specialist streaming person to optimise all the streaming pipelines, then sure hire a specialist.

[0]: https://en.m.wikipedia.org/wiki/Lambda_architecture