>I wonder how much that no-expense-spared, money-is-no-object attitude to buying SaaS impacts an engineers ability to make sensible decisions around infra and architecture
I saw this a lot at a previous company. Being able to just "have more Lambdas scale up to handle it" got some very mediocre engineers past challenges they encountered. But it did so at the cost of wasting VAST amounts of money and saddling themselves with tech debt that completely hobbled the company's ability to scale.
It was very frustrating to be too junior to be able to change minds. Even basic things like "I know it worked for you with old on-prem NFS designs but we shouldn't be storing our data in 100kb files in S3 and firing off thousands of Lambda invocations to process workloads, we should be storing it in 100mb files and using industry leading ETL frameworks on it". They were old school guys who hadn't adjusted to best practices for object storage and modern large scale data loads (this was a 1M event per second system) and so the company never really succeeded despite thousands of customers and loads of revenue.
I consider cost consideration and profiling to be an essential skill that any engineer working in cloud style environments should have, but it's especially important that a staff engineer or person in a similar position have this skill set and be ready to grill people who come up with wasteful solutions.
It is also not a very hard skill. You do a back of the envelope calculation and if your proposed architecture is crazy expensive for your reasonable load, then you have to figure out if you are a special snowflake or just doing it wrong.
What's also frustrating is that a lot of times, costs are hidden from engineering.
I don't know if I would call them mediocre, but without a feedback loop its hard to get engineers to agree whether it's worth time reviewing the code to make it faster compared to just making the db one size larger.