Hi fellow data professional!

The best data skills to develop right now might just be cutting and measuring.

While that statement might be a bit facetious, the hot media narrative is to push the idea of blue collar work as a viable fallback if you’re having trouble breaking into a conventional tech role.

Outlets like CNN have touted the fact that data center engineer is the hottest role in tech.

Executives, specifically Nvidia’s Jensen Huang, speculate that data center construction (despite facing massive backlash around the world) will fuel a “blue collar” gold rush.

The inherent problem in this statement is while it might be true it’s not going to apply to entry-level roles.

Being a tradesman has its own barriers to entry that anyone suggesting “pivot to the trades” conveniently omits.

There are strict union requirements, years of grueling apprenticeships and your prize is decades of backbreaking labor.

Long-term there will likely be opportunities for those with these skill sets, but even blue collar roles will be oversaturated and wages deflated.

Choosing to abandon your current path or “pivot” is no light decision and misleading narratives don’t offer comfort for those who may be experiencing doubt in their future job prospects.

For me, choosing to abandon the liberal arts and pursue a data science masters degree was not a light decision.

I’ve talked about criteria for transitioning, so I’ll end with discussing when and why I hit a wall. Maybe this echoes feelings you’re having in your current profession or role.

Or simply validates the very human need for change.

My “wall” consisted of:

• Un-fulfilling work: Journalism school basically just prepares you to work in local news
• Lack of job security: With more conglomerations scooping up local affiliates, localized media positions don’t have the best job security
• Long advancement horizon: To advance to “big” positions usually requires 5-10 years jumping between smaller markets
• HCOL (high cost of living) relative to low salary: Living in media hubs from New York to LA requires a salary inconsistent with entry-level work; when I interned in NYC I worked two jobs to make ½ rent

Even my “industry leap” happened over 2 years between deciding to go to school for data science and landing my first job.

Inverting these bricks in the wall would provide pretty reasonable expectations for someone seeking to vet a role, org or career path.

Understandably, you’d want work that provides some degree of:

• Fulfillment
• Job security (to the extent possible in this economy)
• Plentiful advancement opportunities over time
• Salaries consistent with the market and that facilitate living in MCOL or HCOL areas

Any industry experiencing a “boom” is unlikely to provide these traits to new hires.

You might be able to nab a high salary building data centers but what’s the longevity there? What is the switching cost to begin a role which might be entirely new to you?

Professional moves are referred to as “transitions” because they happen gradually.

Before you succumb to hype about one industry booming and another going bust, ask yourself how long it would take you to personally gain a foot hold?

Is your personal wall dense enough with reasons to make a drastic move? Or does it make more sense to take a breath and stay the course?

Either path is fine but facilitate your own discovery; a month from now that headline will probably be different.

Speaking of staying the course, if you are committed to navigating the current data landscape without chasing the latest media hype cycles, you need a predictable, production-grade roadmap.

For the past few months, I’ve been working quietly behind the scenes to centralize my entire data engineering career blueprint. I’m talking about taking 5 years of cloud experience, production code templates, and the exact pathway I used to break out of the media industry, and packing it into a single, high-utility resource.

On June 16th, I’m officially opening the doors to a select group of founding members.

If you want to stop patching together scattered online tutorials and learn how to build architectures that actual engineering managers care about, you'll want early access to this.

👉 Click here to get on the early bird notification list.​

More details to come next week.

Thanks for ingesting,

-Zach Quinn

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