13 karma · joined January 13, 2016
- $42k-55k: 2013-2015, Manual Testing@Big Consulting
- $70k-105k: 2015-2017, Lead QA Eng > Dev Team Mgr@Small Niche Consulting
- $110k: 2017-current, Software Eng@Startup
The first step is to stop the bleeding so begin adding unit tests for any new code you write and be sure to factor this effort in with your sprint estimations.
In parallel work top down with high level integration tests written against feature flows. E.g., As a user when I select this then I expect this. This doesn't mean you need to actually use BDD gherkin library for your test runner but at least frame the context of these in that regard since you don't care about the minute details of the underlying code, just the experience of the user story.
And lastly, don't just write tests to write tests, try to understand what is important to cover against because there is nothing worse than maintaining barely useful tests wired up to legacy data fixtures.
Why are you not outraged about this and saying things like 'Harley assisted the military in killing humans for the past 70 years with metal casings that may be used on your softail?'
I mean why stop at google? The private industry has always been supplying the government with goods and services, some of which go to the military.
It is absolutely reachable. A personal path for reference:
2012: Graduated college with a non-comp sci degree (although had tinkered with tech, software, linux, etc since a teen)
2012-2013: Took comp sci MOOCs.. Obsessively learned python and built throwaway projects. Took code challenges weekly.
2013-2015: Got a job as a manual test analyst. Used python to automate testing, got promoted to test lead.
2015-2017: Took a job as Lead QA Engineer. Learned C# for the job. On the side picked up React and Django/DRF for building out SPA/microservices. Began getting serious about clean projects on github and kind of branding myself as a developer (personal landing page, etc). I couldn't keep recruiters off me from my linkedin, stackoverflow and github profiles. Was like ok.. I'm ready... it's time.
2017 (mid): Studied the hell out of algorithms and data structures. Did tons of whiteboarding practice and began taking interviews. Signed up for some tech recruiting apps like hired and opened the recruiter floodgate. I had 2-3 phone interviews a day for 3 weeks. Then a few in persons per week. Not one whiteboard session. Some would send code challenges. The rest asked if I could send them a github project that we'd review during the interview.
2017 (mid)-Present: Now a Software Engineer at an established startup working with brilliant peers and some of my favorite stack.. A massive kubernetes cluster built on Python, Go, React, and ElasticSearch services.
So from 2012-2017 there were many points where I doubted I'd land that dream... and then boom! As soon as I got the balls to throw myself into some interviews for the position I wanted I found it and now I no longer feel like I have to grind away every evening to stay sharp since my job is doing that for me now.
I've also been following this VS Code issue on adding remote docker support for python https://github.com/Microsoft/vscode-python/issues/79#issueco...
However, if you're a hardcore vim guy then I doubt these IDEs are gonna satiate your current flow.
For anyone that has begun the microservice journey, kubernetes can be intimidating but way worth it. Our original microservice infrastructure was rolled way before k8s and it's just night and day to work with now, the kubernetes team has thought of just about every edge case.
That is surely what you attempted to portray with the original comment. That if you want to check the morality at the door you can't work in ANY government financed occupation in the DC region.
Having worked for a government consulting firm in DC, there was a line of business that received funding for social research projects to help inform and ultimately guide government initiatives to improve the welfare and education of certain demographics. This company would be included in your statistic, and there is no moral check needed for that work. While this is anecdotal, it's pretty obvious that a blanket statistic like yours cannot hold up.
99% of statistics are made up and 60% of the time they are accurate everytime.