A couple of rules I have that have worked for me so far is:
Colleagues, tasks, compensation - if at least two of the three are good, it's fine to stay. If not it's time to look for something new.
The first year is a learning year, the second is a productive year, and the third is a "what else can I get out of this place" year. If nothing changes in the third year, then there's not much more to learn from the company and it's maybe time to move on.
Currently working towards the end of a contract/earn-out at a company where people just toss stuff they don't want to deal with over the fence for others to handle with usually zero communication about why/what/how. Just suddenly get a new project with no context. Also, three different bosses in two years because they keep leaving.
Second worst company I've ever worked for.
The worst one involved multiple c-suite executives that would throw objects at employees when they didn't get the answer they wanted. Thankfully I wasn't under contract there and got out ASAP.
While similar, I think the culture more involves the attitudes that's been fostered by the company itself (likely decisions made by their board and upper management).
Most of my colleagues are really nice and friendly one-on-one or even in a group. However, the culture problem is across all departments (~500 employees).
There's a poor attitude that's a result of a perverse options and bonus incentive structure. At least for the software teams, it results in shipping a product regardless of the quality. Essentially, as long as your group ships the bare minimum of something that was planned for that quarter, you get your bonuses.
They're a software company and they don't even have a QA/Test team.
It's a toxic culture and they wonder why there's massive turnover.
Location: Frankfurt, Germany
Remote: Yes, or onsite/hybrid if local
Willing to relocate: No
Technologies: Python, Javascript, Docker, Django, React, GCP, Ansible, Github Actions/CircleCI, Linux, OpenCV, NLP, MLOps, ++
Résumé/CV: Happy to share, just give me a ping
Email: username @ gmail
12+ years experience as a software engineer in small but growing companies, working on medical research, web applications, and data analysis. The last years I've been building pipelines for data scientists and bioinformaticians, with a focus on automation, data quality and reproducability. I'm interested in continuing down this path of working with (data) scientists, but open for suggestions. Send me an email, and let's chat!
I've been happily using Instapaper for this for many years. I add interesting articles to it from all over and then read and highlight in the app/web app right away or later. If I read an article directly, I still tend to add it to Instapaper to keep track of it, espesially if I found it interesting.
Yes, I'm happy with the flow. In Firefox I have a button that adds the article with one click, and in Safari on iOS it's two clicks; share -> instapaper.
Location: Frankfurt, Germany
Remote: Yes, or onsite/hybrid if local
Willing to relocate: No
Technologies: Python, Javascript, Docker, Django, React, GCP, Ansible, Github Actions/CircleCI, Linux, OpenCV, NLP, MLOps, ++
Résumé/CV: Happy to share, just give me a ping
Email: username @ gmail
12+ years experience as a software engineer in small but growing companies, working on medical research, web applications, and data analysis. The last years I've been building pipelines for data scientists and bioinformaticians, with a focus on automation, data quality and reproducability. I'm interested in continuing down this path of working with (data) scientists, but open for suggestions. Send me an email, and let's chat!
Location: Frankfurt, Germany
Remote: Yes, or onsite/hybrid if local
Willing to relocate: No
Technologies: Python, Javascript, Docker, Django, React, GCP, Ansible, Github Actions/CircleCI, Linux, OpenCV, NLP, MLOps, ++
Résumé/CV: Happy to share, just give me a ping
Email: username @ gmail
12+ years experience as a software engineer in small but growing companies, working on medical research, web applications, and data analysis. The last years I've been building pipelines for data scientists and bioinformaticians, with a focus on automation, data quality and reproducability. I'm interested in continuing down this path of working with (data) scientists, but open for suggestions. Send me an email, and let's chat!
Colleagues, tasks, compensation - if at least two of the three are good, it's fine to stay. If not it's time to look for something new.
The first year is a learning year, the second is a productive year, and the third is a "what else can I get out of this place" year. If nothing changes in the third year, then there's not much more to learn from the company and it's maybe time to move on.