I recently cleared the AWS Data Engineering - Associate certification, and I would say that my background as a Solutions Architect at GitLab helped a lot. In fact, almost became an exercise of translating stock knowledge obtained at work.
No, there's not a cheat code, but I came to this realization that prompted me to pursue the certification:
DevSecOps and DataEngineering are virtually the same practice with different workloads.
BOOM. 😳
Being in the space made me see the similarities. Both involve:
1️⃣ - Pipelines & orchestration design
2️⃣ - Automation
3️⃣ - Security & governance
Data pipelines and CI/CD pipelines are really just different flavors of the same thing. In CI/CD, you’re building and shipping code; in data engineering, it’s about moving, transforming, and loading data.
Both need airtight orchestration to keep things running without blowing up. Automation? That’s table stakes in both. Cut out the manual junk and let the system do the heavy lifting.
And don’t get me started on security. Whether it’s code or data, if you’re not locking things down, you’re just asking for trouble. The same rules apply: security needs to be baked in, not bolted on, from the start.
My work at GitLab has given me a perspective on CI/CD, which really ties in very neatly to modern data engineering practices. It’s great how much crossover there is once you start looking at the big picture.
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