The Vision
I want to run a consulting firm some day.
I see myself probably being long-term successful in a fast-paced, varied role like being a self-employed consultant/trainer. With my passion for talking to and helping people, I’d like to manage people, meaning probably I want to operate a consultancy business. Not a sure bet, but maybe probable.
To start a consultancy/training business (or to run an existing one) I need to be able to:
- [✓] Do things that people will buy ( Technical Skills, Product/service Management)
- [~] Convince people to buy those things (Sales & Marketing)
- [✓] Manage and lead people
- [✓] Know how to manage work
- [x] Know how to run a business
- [x] Understand business finances (Finance)
- [~] Communication & Negotiation
The Goal
As for how that affects me now, you need a closer scope.
I’ve long held the view that, until I’m 30, I want to broaden my skills and experiences as much as possible. I don’t want to specialise too hard, because once I do, the inertia will make it harder for me to respond quickly to a future work environment that is not going to hang around.
So what am I doing about that?
Well I’m currently speccing into learning more skills that people will buy. I’m already competent as a Networking & security professional, DevOps & cloud engineer, project manager and solutions architect. I’m also currently in the “data world” - delivering data solutions to clients. So a natural direction to broaden into is data engineering and then data science.
So that’s the goal. In 18 months, I want to have worked very hard and built a load of skills in data engineering, cleaning, manipulation, data pipelines, platforms etc.
Okay, so how do I do that? Well with my current skillset I could fairly comfortably get a job as a Data engineer. But I’m currently an Infrastructure Lead, and I would like also to be able to manage people, to build team plans and execute on business strategy.
So I’m pitching at a Senior Data Engineer/Team lead role. I know I can learn fast, I already have basis in the technical skills and I can bring a bunch of leadership experience.
Now to build a CV to prove it.
The Next Step
To know what to put in a CV, I first needed to know what employers want. So I trawled job search sites for maybe 50 jobs titled “senior data engineer” and pulled all the technical skills.
The list was 16 pages long, so I processed them. I deduplicated skills between job ads, noting the frequency of each skill, as well as whether it tended to be in the “must have” or “desirable”. I sorted by frequency, and what I ended up with looked something like this:
| Skill | Frequency | Must Have |
|---|---|---|
| SQL | 22 | Yes |
| Python basics | 17 | Yes |
| Pandas & NumPY (wrangling) | 12 | Yes |
| MPP & Columnar Databases | 10 | No |
| … | … | … |
| Docker | 9 | No |
| Kubernetes | 6 | No |
| … | … | … |
| Hive/Kafka/Trino | 2 | No |
| Elasticsearch | 1 | No |
This gave me a prioritised list of the skills I should be able to evidence.
Pulling out the skills I already have gives me the best things to put in my CV, and pulling out the skills I don’t have gives me a prioritised syllabus for upskilling as a data engineer!
So that’s what I’ve done. I made a CV. I’m proud of it, and it’s here.
Feedback (or job offers!) very welcome at andrew@acpatt.com .
