ogarten

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Data Engineering, Software Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced data engineer looking for data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Data Engineering, Software Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced data engineer looking for data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request), LLMs, AI Engineering

Experienced data engineer looking for software / data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced data engineer looking for software / data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced engineer looking for software / data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten

Website: https://orellgarten.com

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced Engineer looking for software / data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote | CV: Full CV and details on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten Website: https://orellgarten.com

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling & Pipeline Design, Python, FastAPI, SQL, AWS, Azure, DuckDB, API design (full list on request)

Experienced Engineer looking for software / data engineering contracts to solve business problems.

I usually work on the entire data chain from data generation up to BI or ML use cases at the end. Main focus is data from your business operations (logs, sensor data, process data, ...).

More than 7 years of experience in various industries (Aviation, Automotive, AdTech, ...) where I have helped my clients successfully tackle their challenges.

SEEKING WORK | Germany | Remote or Hybrid (Germany for onsites) CV: on request Email: hello (at) orellgarten.com

LinkedIn: https://www.linkedin.com/in/ogarten/

Technologies & Skills: Software Engineering, Data Engineering, Data Modelling, Data Strategy, Python, SQL, FastAPI, flask, AWS, Azure, PySpark, API design, C++, CMake, ARINC, Linux (full list on request)

Experienced Engineer looking for Software or Data Engineering contracts.

My main goal is to support you in developing great products that require data. From data exploration to fully automating data flow in your products and organization. I have also worked successfully with many custom setups that required data integration and automation

7+ years of experience. Industries: Automotive, Logistics, Aerospace, AdTech

As an experienced software and data engineer, my main expertise is connecting legacy, often custom-developed systems to modern data stacks and infrastructure.

Yes, not saying this is bad at all, just kind of funny. When you think about it it makes sense though. Why wouldn't want someone have a possibility to distribute an efficient engine.

Looks like we are approaching the "distributed" phase of the distributed-centralized computing cycle :)

Not saying this is bad, but it's just interesting to see after being in the industry for 8 years.

Why don't you just try it?

Having a parse-able CV is definitively the most important criterion for your CV though. Ypu don't have to worry about anything else if it's not parse-able '

Disable SSH Agent Forwarding if you want to try this!!

Relevant discussion: https://news.ycombinator.com/item?id=40227624

Ure, if you don't see yourself coding at all or doing technical work, doing consulting in an unrelated things is perfectly fine. I guess it's easier if you already got some experience in the field but at the end of the day the only thing that matters is signing clients

It was okay. I first realized that freelancing might be an option after I was approached by someone on Linkedin to help them with a project and then I had little success with getting more projects but for 2024 I have been booked most of the time.

The things you learn in a startup are mostly applicable to freelancing, too.

I feel you to some extent. I love the challenges and problem-solving but the actual coding part becomes less interesting over time.

I am not quite as far along my career as you but after three failed startup ideas I decided to do freelancing for now. This gives me the opportunity to work on problems that companies really have and while I still code a lot of this is now more focused on the architecture not so much on boring tasks.

Besides that, I also get to see new companies and new projects every couple of months and I am working for myself and not for the secnd vacation home of some boss.

It sounds like consulting could be something you'd enjoy, too.

Also, quitting and finding a new job is really underrated for mental health

Can you provide some more information on what you have worked with?

I find that a lot of people coming from research over-emphasize their research and down-play the engineering side of things that they also had to do in order to do meaningful research.

Anyway, all of this is a continuous spectrum. There are positions that are still closer to research than others but are engineering anyway. In my experience there are little jobs that require you to write papers all the time.

You should think about it like this: What is needed to bring an NLP algorithm to production and which parts of that do I know or don't know.

How does this surprise anyone?

Medical data for AI training is almost always sources in some more or less shady country because they lack any privacy regulations. It's then annotated by a hoard of cheap workers who may or may not have advanced medical training.

Even "normal medicine" is extremely biased towards male people fitting inside the norm which is why a lot of things are not detected early enough in women or in people who do not match that norm.

Next thing: Doctors often think that their annotations are the absolute gold standard but they don't necessarily know everything that is in an X-Ray or an MRI.

A few years ago we tried to build synthetic data for this exact purpose by simulating medical images for 3D body models with different diseases and nobody we talked to cared about it, because "we have good data".

More often than not by working a full-time job somewhere else.

Besides that, there are support contracts, sponsorships and stuff like that, but I'd say there are not a lot of people able to live from that alone.

For an MVP a SQLite database will probably be good enough, too. You make some good points!

Alternatively, go rent a virtual server for a couple bucks a months somewhere

Keep it as simple as possible.

Lambdas and all the serverless stuff is great until it isn't anymore, because you need another service for this and another service for that which gets a) complex quickly and b) expensive, too.

For an MVP, go EC2 or ECS and a database, possibly S3 storage depending on what you need. MVPs are all about learning about the problem in the most cost-efficient way possible

This is great and matches my observations, too.

The people who have some kind of system in their work or life in general are usually the ones ahead of others. Systems allow efficiency and they just get so much more stuff done compared to others.

It doesn't matter if you are an indie hacker, a freelance or a VC-backed startup founder.

You need to talk to (potential) users to understand their needs and problems and offer a solution to that. In the whole indie hacker community it feels like a lot of people build products that target other indie hackers. Not sure what to think of this but they all have similar problems.

However, a lot of products / startups never make any money.

How do you go about deciding what to build?

I am not running a SaaS Platform but I have tried to start several startup so I do have some experience but take it with a grain of salt.

All SaaS that I have seen have some sort of user tracking (mixpanel, amplitude, posthog, ...) which tracks pretty much everything that users do. This can be done completely server-side since you can track all API calls and attach some user metadata to them.

With client side tracking you can do even more, especially when it comes down to UI optimization. Not too big of a fan of that to be honest.

Besides that, user interviews are always great and as a CEO or product manager I would also make an effort to talk to users and take time to gather feedback and just listen to their problems. Staying close to your users is important. Who doesn't like to be heard? However, it's one of the things a lot of startups struggle with or don't see the value in.

Last but not least, if you have only a few users talking to them is the most important thing. Analytics only really work when you user base is large enough. The way to go is to define a set of funnels (what do you expect users to do in what order) and see if these funnels work. Besides that, there needs to be some kind of funnel discovery (what are your users actually doing in what order). The second one if important because it tells you a lot about intentions and gives you a great idea of who to talk to.

SEEKING WORK | REMOTE | I am helping analysts BI professionals to use technical & industrial data

* Location: Germany

* Remote: Yes, I’m self-employed and work remotely.

* Site: https://orellgarten.com

* LinkedIn: https://www.linkedin.com/in/ogarten/

I have done several projects for small and medium businesses and as well as large enterprises. I have build custom data and software solutions (mostly with Python) to ingest , transform and harmonize device and machine data (logs, sensor values, ...) for later analysis.

Open for all kinds of projects. Just send me an e-mail at hello[at]orellgarten.com

So, you got an UI and a backend and the backend more or less makes HTTP(?) requests to other services?

The easiest way to secure the application is probably to use API keys or HTTP Basic Auth to get some basic security. How is your frontend secured? Do people login or can they just access the UI?

A more complicated setup would be OAuth2 but you would need an Auth provider your company may or may not have already. The good things is, your application only lives inside the local network which hopefully makes it less accessible to attacks anyway.

I think everything related to security should be discussed in the team you are working in. You are an intern and cannot know. If you were my intern I would not put you into the position to decide security related things.

Also, why is the UI running in docker but the backend on the host directly? I would run both in docker containers.

1st of all: sounds incredibly controlling.

They could also work on things in their free time and to be honest, as long as they do their work you shouldn't need to care. You only buy 8h of their time usually.

Camera off: Oh shit, I don't want to be watched in larger zoom meetings

Sharing one tab at the time: Crazy. How dare them.

LinkedIn is none of your business. It's their private profile and they can do whatever the hell they want with that.

I am not saying they aren't overemployed but your behavior isn't exactly at its best either.

A good college should teach students how to solve problems and how to think. The major is only a part of that. Computers will likely be around a long time. Computer Science programs also teach AI and all that fancy new stuff.

What else would you focus on? Picking a major should also be about your interests as as student and not about what the parents think. I know this isn't easy, especially if you pay a shit ton of money but you gotta let go as a parent.

I feel this is crazily prevalent in the US that parents cannot let go. Your kids' opinions are often overlooked until they are 18 and then, when they can legally make their own decisions they are not trusted to do so. It's so mind-boggling coming form a European country.

Mh, I guess you got a point. I still stand with what I said more or less though.

While you don‘t always need formal maths it gets much easier when you have a formal education in the field.

Makes a lot of sense from an investment perspective. Essentially only one of these companies needs to become really big to make it worth.

The ones losing out here are the founders most likely.

This is a broad question.

AI/ML needs a math-heavy background and also a lot of domain knowledge to make any sense.

I think the best path for software engineers to go into data is via data engineering or MLOps or whatever it is called tomorrow. This is relatively close to software engineering in many cases, however it's becoming more and more about writing YAML files, too.

What these field could really benefit from though is some software engineering best practices such as testing, linting, formatting and so on.