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Anastasia Khomyakova ❤ for Konfy

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"Couple of engineers can automate tons of work for enthusiasts of scientists", — Pasha Finkelshteyn.

Hello wonderful people!

On the 16th of April, we are running the online Data Love Conference.

You can listen to amazing insights about the world of Data at the @_datalove event.
Check the batting lineup at the Data Love conference. No paid ticket required! Register for FREE!

With this event, we hope to build more personal connections between the audience and our lovely speakers <3. For that, we asked our speakers to share their ideas.
Let’s jump on a wonderful ride of the Data Love world and explore what our speakers have to say.

Our next amazing speaker is Pasha Finkelshteyn, Developer Advocate at JetBrains

Pasha has 15 years of experience in the IT field and tried pretty much everything from Technical support to Data Engineering and management. But it turned out that data is the best thing he's ever worked with.x000D Now Pasha works at JetBrains as Developer Avocado for Big Data and helps to create tools for Data Engineers. Tools to make them awesome!

How did you become interested in Data?

I'm very curious, so data started to interest me when I was an enterprise Java developer. World of Hadoop looked very interesting but quite closed. So I was dreaming of getting there but had no opportunity. When at one of my jobs I've heard that there is a position of data engineer opened for internal candidates I left the Java Team Lead position and became smth like middle data engineer. I had never regret about it.

What are you working on right now? What drew you to your company?

I'm a developer advocate, so programming is not my main work, but I'm the author and maintainer of Kotlin API for Apache Spark. Also, I'm trying to make Big Data Toole Plugin better :)

What is your favorite project or a project that you’re particularly proud of?

Kotlin API for Apache Spark definitely!

Are your projects similar, do they have common focus points, or they can be completely different?

They have only one common point: they're about data engineering. Otherwise, I'm interested in a variety of technologies.

Big data. Cloud data. ML, AI training data, and personally-identifying data. Data is all around us. The world is data-centric. What are some of the industries your clients come from?

Well, our clients are mostly data engineers, but sometimes they are usual developers, who just want to try the Big Data World. I'm quite far from ML, but I'm aware of ML engineers using our tools too.

A lot of people are wondering about Data Engineers and Data Scientists, and the differences between them. What’s your favorite part about your role? What are you measured on? What do you expect when working in a tandem with Data Engineers/Scientists?

My favorite part is Data Engineering. I like to think that a couple of engineers can automate tons of work for enthusiasts of scientists. I hope that scientists will ask engineers how to make things easier to deploy and maintain. And what I measure is T2M on one hand and engineers/scientists ratio on another.

What are the core skills that you think are important in your job, especially if you want to develop your Data Science/Engineering career?

Core Java, GC, the flexibility of thinking, ability to write code in several languages, and love to learn new things.

The industry demand for Data Engineers is constantly on the rise and with it more and more software engineers and recent graduates try to enter the field. Data Engineering is a discipline notorious for being framework-driven and it is often hard for newcomers to find the right ones to learn. What technology are you most excited about? Share top 3 data engineering frameworks to learn, please.

Airflow, Spark, Beam

‘I love working with data because…'

Because it introduces constant challenges in very different fields: approach, architecture, languages, learning.

How did Covid-19 change data science/engineering in 2020?

I'm not sure it did really change anything. Big data is big, it doesn't matter how far you are from it.

What's Your Data Resolution for 2021?

Streaming will become even more important in 2021!

We thank Pasha for the thoughtful answers!

At the conference, he is going to speak on the topic: MLOps: Applying DevOps to ML.

If you want to attend Pashas's talk and to discuss some questions “in person” you can join us on the 16th of April!

The lineup of speakers is incredible. Topics are diverse. Suitable for any level. Interesting Q&A sessions in Spatial Chat. New career opportunities.

Data is all around you.

Register for free
Check out our Website

Join us!

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