Is there an equivalent job title for Data Engineer without the word “engineer”? As a data engineer without an engineering degree I don’t like having that word in my job title.
I'm a third-generation computer engineer and the first one with a degree. I'm half the engineer my father is or my grandfather was. Whatever title you put on your resume is just you marketing the services you deliver. If you can do the work of a Data Engineer, you're a Data Engineer. If you're really self-conscious about it, get a gcloud/aws certification.
The precursor of data engineer was often called ETL Analyst, Data Integration Analyst or Specialist, or even just Data Analyst, to name a few. I also saw Data Integration Developer or similar before. I have always thought, are you an architect, analyst, scientist, engineer or developer? The difference between the last two often being experience and rigor.
What part of the world are you working in? In the US it seems common to switch between software developer and software engineer interchangeably. But in the UK & AUS an engineer title means something completely different.
I suspect almost nobody who does the work of a data/ML engineer has a degree in engineering. Most are computer scientists or statisticians or mathematical scientists. Too few formal engineers choose this path for others to dwell on the term 'engineer'.
The main advantage of using the data engineer label is that it describes what you do now so that others will understand. It doesn't describe your academic past, only your professional present.
What's more, titles like data/ML scientist/engineer are still too new and ill-defined for anyone to worry too much about the exact work implied or the underlying credentials. 'Engineer' is just an attempt to imply that the role involves more involvement in production than exploration.
"ETL developer" was (and still is) the industry term for more than 10 years before this new wave of buzzword spam came along (i.e. when "data science" was "data mining"). Most of these roles focused on using low-code tools like SSIS to build business-focused data transformation workflows faster than with any code intensive approach (e.g. Hadoop ecosystem and derivatives).
Business intelligence consultant/developer was a blanket term used either for 1) people that can model and translate business requirements into data platforms/components; 2) poorly targeted recruiting; 3) more rarely, to describe people that work both in 'frontend' (reporting and dashboarding using tools like PowerBI, who are "data analysts" in newspeak) and 'backend' (ETL developer).
"Data Engineer" today is, sadly, too often synonym with "solving solved problems using an unnecessarily complex approach and toolkit"; and then there are the cases where the volume or complexity of the data actually justifies the cost of using "big data" platforms. Not to sound harsh; the article discussed here illustrates my point using "simple" unix tools: https://news.ycombinator.com/item?id=14401399
