|
| lixtra wrote:
| I'm not aware of any decent data engineer for whom money is the
| bottleneck. It's always time and mental capacity.
| blowski wrote:
| Can anyone vouch for the quality on this site? I've been looking
| for data engineering resources for my team, but don't want to
| share anything shoddy.
| mywittyname wrote:
| Looking over the resources, it doesn't seem worthwhile.
|
| The difficult part is not learning how to code, or work with
| SQL. The hard part is learning the platform and tooling you
| need to operate at scale. The ecosystem is full of tools that
| are great for certain workloads, but terrible for others.
|
| Your best bet is to start by getting an overview of the tools
| available for your team. If you're using AWS, GCP, or Azure,
| they each have data engineer-oriented certifications. So take a
| look at what tools those certification courses cover and start
| there.
|
| If you are not in a cloud environment, take a look at Apache
| Airflow, Beam, Storm, or Hadoop. Most of the tooling provided
| by the big cloud providers is either a rip off of one these
| products, or is merely a hosted version (i.e, GCP Cloud
| Composer is managed Airflow).
| gigatexal wrote:
| My title says Senior Data Engineer* and from what I can tell it
| looks like a collection of interesting things but nothing so
| revolutionary. You're better off identifying what aspects your
| team is weak in and seeking out experts or training in that
| specifically.
|
| * titles are kinda shit analogs for skill
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