Ask HN: How to pivot from one field to another?
11 comments
I would start by asking "What is my purpose in seeking to make a switch?"
Knowing your 'why' will help you know for sure if you are able to make the commitment required to make a switch. In general it will take a non-trivial amount of effort to make the change.
If you are confident that you genuinely want to move to the new field then it is all about learning and growing the skills required.
Get 1% better every day in that field and within a reasonable amount of time you'll have the proficiency to at least get entry level position.
Best of luck to anyone on this path!
Knowing your 'why' will help you know for sure if you are able to make the commitment required to make a switch. In general it will take a non-trivial amount of effort to make the change.
If you are confident that you genuinely want to move to the new field then it is all about learning and growing the skills required.
Get 1% better every day in that field and within a reasonable amount of time you'll have the proficiency to at least get entry level position.
Best of luck to anyone on this path!
Here's how I switched from data analyst -> software engineer. I don't do much DevOps, but maybe it'll help anyway. To avoid qualifying every statement, just pretend I wrote "in my experience" or "for me" after each assertion.
As a prereq, try to make sure you enjoy the field you're switching to. This seems obvious, but I've met people that didn't. Learn concepts and build projects in your target field to make sure you're actually interested. I built some silly projects with Node & React, learned enough C#/Unity to make awful 2d games, and solved Project Euler/Exercism puzzles. I started 20x more projects than I finished, but finishing isn't really the point at this stage - you're just aiming for exposure. Once I knew what I wanted, I made a plan and started to execute:
1. I positioned myself to program as much as possible at work. In my org, this was easy - most analysts were already writing Python, R, or SQL every day. I took every opportunity to work on projects where the deliverable was working software instead of a slide deck. Almost every data analyst chose the opposite - so there was little competition for these projects. For example, I ended up being able to debug and fix a production C++ application, just because everyone else avoided the task and I offered to try. This step lasted about 1.5 years for me.
2. I learned and built things in my free time. I read books, watched tutorials, did algorithm MOOCs, etc etc. If I had to do it again, I would spend 1/5 the time (or less) following step-by-step tutorials. They definitely helped (especially with "unknown unknowns"), but stumbling through the silliest of projects helped me retain so much more. I did this in parallel with step 1.
3. I did a CS degree. I detailed my cost-benefit analysis in a blog(1), so I won't regurgitate it here. I don't think this is necessary, but being able to apply to new grad SWE jobs was a boon. I tried making the switch before doing a CS degree and got filtered at the resume stage almost every time. I think degree gatekeeping is dumb, unfair, etc. but it is a real problem constraint that you should consider.
I hope any of this helps. It has been a lot of work, and a lot more work to go...but I'm 100% sure I made the right choice. My email is in my profile if you think there's any help I can offer. Good luck!
(1) https://mdrake.sh/blog/whats_next/
As a prereq, try to make sure you enjoy the field you're switching to. This seems obvious, but I've met people that didn't. Learn concepts and build projects in your target field to make sure you're actually interested. I built some silly projects with Node & React, learned enough C#/Unity to make awful 2d games, and solved Project Euler/Exercism puzzles. I started 20x more projects than I finished, but finishing isn't really the point at this stage - you're just aiming for exposure. Once I knew what I wanted, I made a plan and started to execute:
1. I positioned myself to program as much as possible at work. In my org, this was easy - most analysts were already writing Python, R, or SQL every day. I took every opportunity to work on projects where the deliverable was working software instead of a slide deck. Almost every data analyst chose the opposite - so there was little competition for these projects. For example, I ended up being able to debug and fix a production C++ application, just because everyone else avoided the task and I offered to try. This step lasted about 1.5 years for me.
2. I learned and built things in my free time. I read books, watched tutorials, did algorithm MOOCs, etc etc. If I had to do it again, I would spend 1/5 the time (or less) following step-by-step tutorials. They definitely helped (especially with "unknown unknowns"), but stumbling through the silliest of projects helped me retain so much more. I did this in parallel with step 1.
3. I did a CS degree. I detailed my cost-benefit analysis in a blog(1), so I won't regurgitate it here. I don't think this is necessary, but being able to apply to new grad SWE jobs was a boon. I tried making the switch before doing a CS degree and got filtered at the resume stage almost every time. I think degree gatekeeping is dumb, unfair, etc. but it is a real problem constraint that you should consider.
I hope any of this helps. It has been a lot of work, and a lot more work to go...but I'm 100% sure I made the right choice. My email is in my profile if you think there's any help I can offer. Good luck!
(1) https://mdrake.sh/blog/whats_next/
I did this from IT technician to DevOps/Platform engineering. Took about a year of learning and a handful of failing interviews to finally have someone take a chance on me.
I started by first learning what the job requirements are, looking deeper at the software stacks and where they are used. Eventually, I figured out that AWS, Azure, and GCP give you a handful of credits to try things out. From there, I started to learn and setup my own environments. Eventually, I got good enough to understand how to setup my own applications with best practices in mind.
I started by first learning what the job requirements are, looking deeper at the software stacks and where they are used. Eventually, I figured out that AWS, Azure, and GCP give you a handful of credits to try things out. From there, I started to learn and setup my own environments. Eventually, I got good enough to understand how to setup my own applications with best practices in mind.
May I ask, why do you want to change? working in the data field myself, sometimes I find my work useless and meaningless
That’s a good question,
I believe working with infrastructure is much more fun compared to data, this is just my opinion
Also you are making wider impact as you are pretty much in charge or directly making impact on the infrastructure
Also you are making wider impact as you are pretty much in charge or directly making impact on the infrastructure
This is a general question but I think it is about practice. In your organization, you can just start working on DevOps related problems and issues. Working in a startup helps as you do not have to get granted permissions just to work on DevOps.
As always practice makes perfect. In the meantime you can watch videos on Youtube
As always practice makes perfect. In the meantime you can watch videos on Youtube
Build a ramp from where you are to where you want to go. List all the things you do as data analyst, every little thing. List all the things DevOps do, every little thing. Now find the things that are common between the two, that is the ramp you need to take and build upon.
And look around for places where your company needs a data analyst for a devops project, or needs devops for the data analysts. Ask to be put on those projects.
Coursera, Team Treehouse, YouTube.
Make a list of qualifications for the perfect DevOps person. This can be from knowing people in the field, or from want ads, or from career planning web sites.
Then start earning those qualifications. What certifications can you get? Do you need another degree?
Finally, make the jump to a job you are qualified for in your new field. You will probably take a pay cut in the short term.
Don't overlook transferring to a DevOps position with your existing employer.
Then start earning those qualifications. What certifications can you get? Do you need another degree?
Finally, make the jump to a job you are qualified for in your new field. You will probably take a pay cut in the short term.
Don't overlook transferring to a DevOps position with your existing employer.
I’ve shifted careers a few times now accounting > dev > design.
What I look for now is working out within a new career what defines the essence of the excellent craftsperson at that craft. Certain practices, mindsets, and the hard things to understand and master. I focus there and become valuable quickly. I obviously can’t immediately master then but I’m hungry curious about them, asking why do you guys think this is so important? How did you all learn it? What’s the edge we’re mastering next? All help me hit the ground running.
What defines an excellent committed person in this field from an ok one? Being deeply focussed on how to master the craft opens doors and you transition more easy.
What defines an excellent committed person in this field from an ok one? Being deeply focussed on how to master the craft opens doors and you transition more easy.
This question might too broad but what I mean here is that let’s say you are a data analyst but want to move into DevOps related field or Vice versa.
How should one be able to make a switch?