I started a new job

Short personal update

This article is a short personal update. I’m not a fan of talking in the first person in blog posts, so be warned — this post has an exceptional amount of I’s 👀.

Before 2023

Over the last couple of years, I was lucky to carve a niche for myself, which lies at the intersection of data engineering, cloud/serverless, technical writing, technical support, community management, and, inadvertently DevRel.

Most of my past jobs were similar with respect to key domains: they involved working with data warehouse and cloud infrastructure, SQL, Python, serverless (mainly AWS), workflow orchestrators (a lot of them), and many forms of communication. The communication part included consulting, blog and social media posts, technical tutorials, release announcements, meeting and hiring people, 1:1s, and supporting users across various channels.

Choosing a career in the 2023 data startup market

I interviewed at several companies providing either pure SaaS or hybrid SaaS and open-source products. In the end, three aspects influenced my decision:

1. I love working at startups, but amidst the current market situation, joining a (too) quickly growing SaaS startup entails a high risk of layoffs. For DevRel positions, I prioritized smaller startups with an open-source core product. Even if the company has to discontinue its commercial offering due to the currently challenging market situation, the open-source version (and the work the team will put into the product, teaching, and spreading the word about it) will likely keep providing value to some people. Orchest discontinuing their Cloud product is a great example — the open-source product is still there.
2. AI and related tools are improving every week, encouraging further enhancing “softer” skills, including product and people management, more ways of content creation, and public speaking. In the face of AI automating so many tasks, those skills seem more important than ever to prioritize.
3. Opportunity to switch to a part-time job. As someone living in Germany, I took it for granted that you could always turn your full-time job into a part-time job. It turned out that it’s not always a guarantee in the international job market. When I asked during interviews whether it would be possible to switch to a part-time job after a couple of months, I was quite surprised that many companies refused to provide that as an option.

Why Kestra?

At Kestra, I can use and further improve my skills in data engineering, workflow orchestration, data infrastructure, product, content, and community. Kestra (as a product) is open source (criteria #1 ✅). The company offered me a role with a lot of autonomy and an opportunity to help with product management (criteria #2 ✅).

I enjoy embracing change and learning about new cultures. So far, I’ve worked primarily for German and US companies. I’m curious about what working for a French startup will be like. Kestra was also one of the few companies that agreed to a part-time position.

Finally, Kestra is an underrated product. It’s easy to use, scalable, and fast. And yes, you can use Kestra to orchestrate Python tasks, even though the workflow definition is in YAML (more on that soon). I’m still interested in helping solve the problem of data/workflow orchestration. I hope that the planned features and plugins on Kestra’s roadmap and the upcoming content will help you in some way in your data engineering lifecycle.

Next steps

I’ll post tutorials and video demos soon to demonstrate what you can do with Kestra. If you are interested, follow me here on Medium, LinkedIn, and my recently launched YouTube channel.