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Minor copy edits from a second proof-read

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R Tyler Croy 2019-08-22 16:44:29 -07:00
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_posts/2019-08-22-platform-engineering-at-scribd.md
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@ -28,7 +28,7 @@ Platform Engineering are:
applications and data.
* **Data Engineering**, treats data as a product, ensuring that high quality
data sets are accessible to internal users.
* **Ruby Infrastructure**, helps Scribd adopt or upstream major ecosystem improvements
* **Ruby Infrastructure**, helps Scribd adopt or upstream major ecosystem changes
which will improve organizational and operational performance of Ruby and
Rails.
@ -38,7 +38,7 @@ Tools teams where the edges of our respective responsibilities lie is one of
those good healthy debates every organization should have as it grows. A year
ago much of engineering was flat with lots of generalists, compare that to
today where both Product and Engineering groups are learning that
specialization when appropriately applied can be helpful.
specialization when appropriately applied can be quite helpful.
What has also been personally challenging about hiring in Data Engineering is
my relative inexperience in the field. My jam has always been backend service
@ -48,11 +48,11 @@ lot of work to do, changing from a mindset of "dumping in the data lake" to
where Product and other parts of Engineering are viewing data as a more
integral part of their work. Both in generating clean data but also by
utilizing derived data sets to make more personalized or responsive user
experience.
experiences.
The barriers between "data platform" and "production engineering" remind me of
the now outdated silos between application developers and operations engineers.
DevDataOps. Maybe DataDevOps?
I'm not sure what to call it, DevDataOps? Maybe DataDevOps?
I'll have to figure out the hashtag later.