Women in technology play a critical role in driving innovation and progress in the industry. As technology continues to shape every aspect of our lives, it is essential to have diverse perspectives and experiences at the table to ensure that the products and services being created are inclusive and meet the needs of all users.

In hopes of inspiring the future generation of women in technology, a few women from Snowflake’s Cognitive Services team based in Warsaw, Poland, share how they started in the tech industry and what skills they found helpful early in their careers.

Meet the Women from Snowflake's Cognitive Services Team:

Dobromiła Doktór, Software QA Engineer
Marianna Janczak, Software Engineer
Alicja Wójcicka, Research Scientist

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What inspired you to pursue a career in IT, and what are some of the most exciting projects you’ve worked on?

Dobromila:

A former partner, who is also a programmer, convinced me to start a career in IT as a Tester. I began postgraduate studies called 'Software Tester' and so it all began for me.

Most exciting projects…Once I worked for a U.S. company with offices across Europe. As a group of testers, we traveled to some EU countries where I met new people, learned many things, and increased my knowledge. Another fun project was creating an accessible e-commerce web page.

Marianna:

I've always been into computers (mostly games) and kind of interested in programming, but I've studied economics and worked in finance (and other office jobs) for 12 years.
I used to be really into finance, but as it evolved and became more and more virtual, I decided I needed to change my job. We spend too much time at work doing something we don't like. So I started IT studies, and in the third year, I looked for a job in programming to do what I love. I had no commercial experience in IT, so what I did for my Curriculum Vitae (CV) was showcase my private projects which included some machine learning, websites, and a game in python.
And that's how I got a job at Applica , which was later acquired by Snowflake in 2022.

Alicja:

I am a linguist by education and as a linguist, I have been exploring the secrets of meaning in natural language for many years. I also participated as a linguistic expert in many IT projects - both commercial and scientific - aimed at the development of natural language technology.
As a person working on the border of two worlds: humanities and new technologies, I saw the benefits that both these fields can derive from cooperation. I started my career in IT quite late, but it was a special moment, a time when many methods of modern Natural language processing developed, with large language models based on the transformers architecture at the forefront.
At that time, I was still working as a linguist, but from the perspective of my workplace, I could observe what my colleagues were doing, and it was fascinating! I started learning programming and data science, and a few years later changed my position from a linguist to a data scientist.

One of the largest and most interesting projects in which I participated is the implementation of a system for the automatic processing of court and bailiff documents in a large Polish financial company. As part of the system, we have developed many different models for classifying documents and extracting various information from them.

What do you think are the most important skills for your role to possess?

Dobromiła:

SDET - Software Development Engineer in Test
The most important skills are to question everything, to not take things for granted and not to get used to how everything works.

Another thing would be to be very communicative. Working in IT, we have to talk a lot with people, consult, share knowledge, discuss what and how things should be done, as well as ask and specify the conditions under which the tests should be carried out.

Marianna:

I'm a developer, I do frontend and backend, JS, and Python. I think for this kind of job, the most important skill is the ability to learn and adapt. To constantly look for better ways of not only writing the code but of solving problems, too.

Alicja:

Apart from programming skills and a good knowledge of statistics and ML, I would say that a data scientist should be very focused on... data.

Pay a lot of attention to detail, be inquisitive, and look at data carefully, suspiciously, and from different perspectives. Cleaning data also requires a lot of patience.

Don’t be afraid to experiment and try different methods to solve the problem. Last but not least, this is a job that requires cooperation with the team, both with other data scientists and business analysts, so that the result of our work best meets the needs of our clients.

What advice do you have for people who are just starting out in the tech industry, and how can they best prepare themselves for a successful career?

Dobromiła:

Do not get used to the environment you are working in, whether that’s with the software or the people.

Question everything and everyone...well almost everything, but yes. Do not be afraid to ask so-called 'stupid' questions, some of those are 'brilliant' and give a totally different view on the subject. And yes, you will learn almost every day something new, each and every single project is different from the previous one.
Don't give up if you don't understand something, ask one, two, or five people, and find someone who speaks 'your' language. Don't forget, some brilliant people may lack teaching skills, that is nobody's fault. Apologize if justified but no more than that, software issues are not your fault.
Be brave and confident when talking, we often lack it. Other than that, be open minded, have fun, and enjoy what you do.

Marianna:

My advice is to do what you love, then you will do it well. I've gained the skills I needed to enter IT by writing my own projects. And I didn't care if they seemed quite complicated in the start - it just took some more time to pursue them, but I gained so much more knowledge this way.

Alicja:

There are a lot of different career paths in IT, so I think it would be good to know which one of them interests us the most and is in line with our predispositions. You have to be open to acquiring both knowledge and the necessary technical skills. It is a good idea to contribute to open source projects, and - in the case of data science - to try your hand at solving ML problems, e.g. by participating in open online competitions.

The opportunity to learn from others is also invaluable. Being in an environment where learning, personal development, and knowledge sharing are valued really helps a lot. I wouldn't be where I am if it wasn't for the support and help of my colleagues, who believed in me, set me new challenges, and cheered me on my way toward data science.

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