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Data Engineering Meetup (подія в архіві)

Took place
23 November 2019 (Saturday)
Place
Kyiv, Volodymyrska 101, LIFT99 Kyiv Hub
Price
free
Attendees

𝗣𝗲𝗼𝗽𝗹𝗲.𝗮𝗶 helps sales, marketing, and customer success teams uncover every revenue opportunity from every customer.
We’re on a mission to be the AI platform for all business activity across every organization.

We want to contribute into the Engineering community and share our knowledge and experience!
If you want to know what we’re building, how we’re building it, and- most importantly — meet the people who are building a great product join our Data Meetup!
Come and listen to our absolute best-talented engineers on Saturday, November 23rd, 2019 ;)

𝗘𝘃𝗲𝗻𝘁 𝗦𝗰𝗵𝗲𝗱𝘂𝗹𝗲:

11:00 [45 min] Kostya Tsykulenko, Senior Software Engineer
𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗱𝗮𝘁𝗮 𝗹𝗮𝗸𝗲 𝗶𝗻 𝗔𝗪𝗦

11:45 [15 min] coffee brake

Noon [45 min] John Wulf, Principal Engineer & Team Lead
𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗱𝗮𝘁𝗮 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗶𝗻 𝗮 𝗳𝗮𝘀𝘁-𝗴𝗿𝗼𝘄𝗶𝗻𝗴 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗳𝗼𝗰𝘂𝘀𝘀𝗲𝗱 𝘀𝘁𝗮𝗿𝘁-𝘂𝗽

12:45 [1hr] Lunch — networking

14:00 [45min] Artem Vysotski, Staff Engineer
𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗣𝗲𝗼𝗽𝗹𝗲.𝗮𝗶 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 - 𝗹𝗲𝘀𝘀𝗼𝗻𝘀 𝗹𝗲𝗮𝗿𝗻𝗲𝗱

15:00 wrap up, networking time

Due to the limited number of seats, there will be a selection of registered participants.
So please fill the registration form, and we’ll send you the confirmation letter by November 18th.

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Today we are closing registration and starting the selection of registered participants.
Please check your mail for a confirmation letter 🙂
See you this Saturday at Lift99 Kyiv Hub at 10 am 👍

If you didn’t receive a confirmation letter or had no chance to register on time — please contact [email protected]

John Wulf, Principal Engineer & Team Lead

Since joining People.ai almost 2 years ago, John has been evolving People.ai’s data infrastructure, focussing on driving business value, scale and cost.
He has more than two decades of experience as a software engineer and engineering manager working at anything from three-person start-ups to Fortune 500 companies. In the last 8 years, he is focussing on data-related projects in San Francisco in areas like IoT, financial and advertising space for start-ups including Twitter.

One of the key challenges in fast-growing successful business-focused start-ups is understanding how to scale technology and how to manage tech debt that is inevitably accrued as a company grows faster and faster.
Building data pipelines that usually require a heavy upfront investment provide even a greater challenge.
In this talk how to evolve a data platform iteratively to support business growth John will talk about:
What are the technical debt trade-offs?
How can you manage your technical debt?
What problems need to be addressed or they will kill you down the road?
What are the signs that you are heading for disaster?

Artem Vysotski, Staff Engineer at People.ai
Topic: Building People.ai Infrastructure — lessons learned

Artem has joined People.ai in early 2017 to build the first version of the infrastructure and CI/CD platform on top of Kubernetes. Since then, it has significantly evolved to support 5x team growth and the addition of the data science (ML and AI) and data teams (Big Data). Artem will take you through this exciting journey and along the way, will tell you the story about the adoption of Dev Ops culture and key lessons learned.

Throughout his almost 3-year tenure at People.ai, Artem held multiple roles as an IC and a manager: from being responsible for Infrastructure and Platform to Security and Compliance and Product Development.

Before People.ai, Artem founded 300Editors.com, which was successfully acquired in 2017 by a private company.

Join Artem’s presentation to hear the story of People.ai’s infrastructure evolution.
On top of that, Artem will gladly cover any non-infra related areas such as security, compliance, and product development.

Registration form: forms.gle/pSUmXVcEYDc7Hdyg8

Meet our first speaker: Konstantin Tsykulenko
Senior Software Engineer at People.ai
Topic: Building a Data Lake in AWS

Konstantin is an engineer on the People.ai data infrastructure team, working on scaling the company’s data platform to support growth goals and provide a solid foundation for ML components. He recently led the initiative to overhaul most of the batch data processing in People.ai by implementing a data lake, which resulted in major performance improvements and infrastructure cost reduction.
He has almost a decade of experience in software engineering with five years of experience in startups, having worked on a wide variety of problems ranging from data engineering to designing scalable distributed servitized architectures both as an individual contributor and as an engineering lead.

In this talk, you’ll learn about People.ai’s journey to the separation of batch analytics and operational stores and how to build a production-grade data lake.

You will find answers to the following questions:
— What is a data lake any why would you need one?
— What is a cost-effective way to do batch analytics?
— How do you handle mutable data and data reprocessing in append-only storage?

Registration form: forms.gle/pSUmXVcEYDc7Hdyg8

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