Ageism in Tech and Data Science
Observations on pay and career growth

I pull a lot from my personal observations having worked in Silicon Valley as an engineer for 12yrs, as a Wall Street technologist for another 12, and more recently in MBB consulting. I’ve managed and hired shy of 200 people in my career. That being said, a lot of this opinion or anecdotal but has some backing by research [5,6].

1: Demand is limited for high paid engineers

Engineers get paid well, but you hit a ceiling relatively quickly (a few outliers exist namely at FANG firms). Also important to know demand drops quickly as you move up the curve — it is natural you leverage talent in pyramid structure for most teams.

Common salary/demand for engineers

2: Pay curves for leadership are higher

Engineer pay largely cap out at Sr levels, overlapped by leadership including Tech Leads and Managers, up to CTOs. The lines start/end abruptly because roles simply don’t exist at some levels (Anyone hiring Jr CTOs?).

3: Senior leaders are overpaid (but are not technical at all!)

I’m sure we all joke about the clueless Sr Leader/CTO/CIO who hasn’t coded or done anything technical in decades. It is all too true in many industries. Their ability to get things done at scale is what distinguishes them and gets them the big $$$.

So what? What is the point?

If you care about keeping your job and making more money than timing your career moves is key. A 28 year old manager will have tremendous bias against them and their decisions, while an engineer at 48 will have people questioning your abilities. The trap that often happens is being stuck in middle management — no longer technical and also not developed as a strong leader.

Presented next is a playbook to help move up the ranks. Unfortunately even this playbook exhibits ageism and is intended for younger people!
['Doug Foo']
['Age Discrimination', 'Career Paths', 'Technology Management', 'Career Advice', 'Ageism']