Data Engineering Concepts

Dmitrii Polovinkin
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  • Technology
  • Updated Biweekly

Welcome to the first purely educational podcast about Data Engineering in English, I'm your host Dmitrii Polovinkin! This is a podcast about tools, technologies, and ideas that we data engineers work with every day. In relatively short episodes I break down one topic at a time - describing how modern data stack works, giving you explanations based on the real-world context and lessons from my 7+ years of working in as a data engineer in the variety of fields and projects. Subscribe to start learning and become a better data engineer! :)

Episodes

  1. 6d ago

    Data Systems Requirements: What to Define Before You Build

    What should you define before designing a data system? In this episode, I cover the key requirements every data engineer should think about - from data sources, consumers, volume, throughput, and latency to availability, RTO/RPO, retention, compliance, data correctness, and budget.

  2. Sep 23

    Database Indexes: How They Work and their Main Types

    Database indexes are one of the most important tools for improving query performance - but there are many different types, and the differences between them are not always obvious. In this episode, I explain how indexes work, what's their benefits and drawbacks, and I go through the main index types and concepts: B-tree and B+ tree indexes, dense and sparse indexes, bitmap and hash indexes, clustered and non-clustered indexes, composite and covering indexes, as well as duplicate and redundant indexes. There also details about why column order matters in composite indexes and how an index-only scan can avoid reading the table altogether - just as an example. This is a solid and practical high-level overview for data engineers who want to better understand indexes for both everyday work and technical interviews.

  3. Sep 16

    Apache Airflow: Core Concepts and Building Blocks

    Hi, my name is Dmitrii Polovinkin, I'm a data engineer with ~7 years of experience (check out ⁠⁠my LinkedIn⁠⁠) and welcome to the first episode of Data Engineering Concepts, which is a new educational podcast about data engineering, designed to be useful when you're learning on the go. In this episode, I explain what Apache Airflow is, what problems it solves, and when it makes sense to use it in data engineering. We go through the main Airflow concepts, including DAGs and DAG runs, tasks and task instances, operators, sensors, hooks, connections, variables, scheduling, data intervals, XComs, and trigger rules. I also give a high-level overview of Airflow architecture, executors, workers, the metadata database, and some of the key DAG configuration parameters.

  4. Sep 5

    Pilot - Welcome to Data Engineering Concepts

    Hi, my name is Dmitrii Polovinkin, I'm a data engineer with ~7 years of experience (check out ⁠my LinkedIn⁠) and welcome to the pilot episode of Data Engineering Concepts, which is a new educational podcast about data engineering, designed to be useful when you're learning on the go. In this episode I explain why I started the podcast, about my experience as a DE, who it is for, what topics future episodes will cover, and how I plan to approach them. If you're a data engineer or interested to become one, work in a related field or preparing for interviews - subscribe, this podcast is for you! This is episode zero is recorded in Da Nang, Vietnam 🇻🇳.

  • 4 Episodes

About

Welcome to the first purely educational podcast about Data Engineering in English, I'm your host Dmitrii Polovinkin! This is a podcast about tools, technologies, and ideas that we data engineers work with every day. In relatively short episodes I break down one topic at a time - describing how modern data stack works, giving you explanations based on the real-world context and lessons from my 7+ years of working in as a data engineer in the variety of fields and projects. Subscribe to start learning and become a better data engineer! :)

Information

  • Creator
    Dmitrii Polovinkin
  • Years Active
    2026
  • Episodes
    4
  • Rating
    Clean
  • Copyright
    © Dmitrii Polovinkin
  • Show Website
    Data Engineering Concepts