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Level up your Data Engineering skills with EPAM Master's Program 

Big Data concerns ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Obtain the necessary theoretical and practical background that covers best engineering practices, resulting in a productive software development process along with product quality and aimed to improve the expertise in Big Data and prepare for real-time Big Data projects.

Whу this Program?

Big Data basics

Learn about data engineer responsibilities, what data is, types of data, how to process and work with data, and specifics of data systems and architectures.

Best approaches and practices

Understand the specifics of working with data in analytic, streaming and ML systems including such frameworks for batch-oriented analytics as Spark, Hive, Hadoop based ecosystems; for streaming - Kafka, Flink, Spark; build pipelines, work with this toolset and know what and when to use them.

Up-to-date information and hands-on experience

Have grounded knowledge in cloud computing, understand when to use on-premises or cloud technologies, and know the toolset of a data engineer in the cloud including such tools as Databricks, HDInsight, Event Hug in Azure, Dataflow, Dataproc in GCP, Glue, Athena, EMR in AWS.

Skills You Need to Succeed in Course

3+ Years of Experience
Working in IT as a software engineer or in a technical oriented business role
Knowledge of a Modern Programming Language

Java, JavaScript, Python and/or C#

Knowledge of English
B2+ (Upper-intermediate)
Soft Skills

Solid communicator,
humble leader, and team player
eager to learn

Study Plan

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  • Data Engineering

    The course is aimed to prepare the students for real
    Big Data projects. During studying the course students
    will make deeper dive into Hive and see which additional features can be used to increase Hive performance;
    have an opportunity to improve their skills in Apache Spark; discover the use cases for Spark Streaming and overview which problems it is aimed to solve. What is more,
    students will get acquainted with the Kafka software platform and see how it is implemented by large
    well-known companies; extend their knowledge about streaming data processing by exploring the frameworks which are commonly used for this purpose. Also, students will get acquainted with main workflow management tools, learn about NoSQL Big Data Family, and have a detailed look at Elasticsearch engine.

  • Project-Based Training
    Project-based training helps to familiarize with the real industry standards of IT projects in the software development enterprise, gain valuable practical experience, and apply theoretical knowledge in real life.
    Training will allow the students to dive deep into core knowledge about enterprise IT project setup and get details about specialization chosen by students.

About This Learning Course

  • The program lasts 6 months
    and includes 2 modules.

  • Certificate is provided for each program module
    and for the whole program.
  • 25% of contact hours with leading industry experts
    75 % learn by doing gaining theoretical knowledge and hands on experience on the interactive digital platform.

Learning Objectives

  • know the reasons why the Hadoop platform is popular through its main advantages; understand the benefits provided with the latest versions, be able to install
    the Hadoop and have basic skills in Hadoop navigating effectively, get familiar with the architecture and basic real Hadoop use-cases;

  • have deep knowledge of Hive functionality, understand
    User Defined functions in Hive and know the main use cases, be familiar with ACID Transactions, have grounded skills, and know how to use three types of statistics for Cost Based Optimizer and which optimization technique to apply to increase Hive performance;

  • be familiar with the flow-based programming concept, understand what Apache Nifi Project is and be able to automate the flow of data between software systems, use StreamSets Data Collector;

  • know the general characteristics of messaging systems and their types, understand what Kafka is, its main use cases, capabilities, architecture, and main components, have grounded skills and know how to use Kafka Connect framework in order to see which problem it is aimed to solve as a part of Kafka ecosystem;

  • use Oozie, Airflow, and Jenkins pipelines workflow management tools, understand its features and work mechanism, architecture, and main components;

  • understand the Apache Spark framework; know the roles of Catalyst Optimizer and Tungsten project in increasing the Spark’s efficiency; be familiar with Spark Streaming and know how to use it for steaming data analysis, have a deep understanding of the concept and features of Structured Streaming;

  • have a clear understanding of streaming data processing and know how such data can be used for analytic goals, have meaningful knowledge of Kafka streams library, and understand how it can be used to build applications and microservices where the input and output data are stored in Kafka clusters;

  • be familiar with NoSQL alternative to traditional relational databases, understand the difference of NoSQL from RDBM, know the key features, architecture, main use cases, and competitive advantages of NoSQL databases such as Cassandra, MongoDB, and HBase;

  • have a deep understanding of Elastic search features, functionality, architecture, and components, know its advantages, be able to install Elasticsearch and use basic commands as well as know how to control querying results;

  • be familiar with cloud-based solutions, have comprehensive knowledge of cloud computing, networking, identity, and security as well as have deep understanding of Big Data processing based on cloud infrastructure and serverless approach;

What You'll Learn on Data Engineering

The program includes 11 submodules and will help students to obtain the best practices and approaches of working with data, provide with up-to-date knowledge and practice while getting feedback from professional trainers and mentors.

  • Introduction into Data

  • Hadoop

  • Hive

  • Spark

  • Kafka

  • Streaming

  • Data Movement

  • Cloud

  • Workflow

  • NoSQL

  • Elasticsearch

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Our students have the opportunity
to obtain Master's Degree Diploma

Our students from Ukraine have an opportunity to choose Specialization Program in partnership with one of the leading universities. Within this option, Program modules are counted for MS programs, and students can obtain a Master's Degree diploma.
Partner Universities in Ukraine:
  • Lviv Polytechnic National University​
  • National Technical University “Kharkiv Polytechnic Institute”​
  • National aerospace university “Kharkiv Aviation Institute”​
  • Kharkiv National University of Radio Electronics​
  • National University of Kyiv Mohyla Academy​
  • State University of Telecommunications​
  • Kyiv Academic University

Register for the Big data program

FAQ: studying flow

  • Is it possible to study online?

    Yes, both programs and universities offer an online format.

  • Is it possible to study and work at the same time?

    Yes, the Program and universities created a curriculum comfortable for combining working with studying.

  • Do I need to pay for the education at the university additionally to paying for the program itself?

    Yes, if you are not eligible for a state form of education.

  • How many hours per week will I spend studying?

    Up to 20 hours per week is the time you are supposed to spend studying on the program: 75% self-studying and 25% online sessions.

Pricing and Discounts

Price options for the program

Full price


Price per module


20% Discounts

for EPAMers 

10% Discount

if paying for the whole program in one payment

FAQ: payment flow

  • Is there an option to pay in parts?

    Yes, you can pay for each module separately (instalment payment).

  • When do I pay if I choose the instalment payment option?
    When choosing this option, payment should be made within the first two months after the program start.
  • Do I still have my 20% discount
    if I pay in parts?

    Yes, sure.

  • Can I add my 20% discount and 10% for one transaction payment?

    Yes, you can.

  • Is there a refund if my plans change?

    Yes, there are several cases that allow refunding. As well, individual plan of studying can be considered.

  • Do I need to sign anything offline and come personally?
    No, all the documents are signed online.
  • What is my deadline to make up my mind and pay?

    You should sign the contract and make the first payment 6 working days before the program starts.

  • Do I need to pay for the education at the university additionally to paying for the program itself?

    Yes, if you are not eligible for a state form of education.

See what people say

"I was taking a technical expertise course, but I took a strong interest in the product management module. We learned how to start the project, plan the development process and build a business model for the product. I even came up with ideas for my own projects."

Kirill-Beresnev 1 (1)
Artem Kobrin, last year's graduate

"After only a month of studying, I was given a new position and a salary 30% higher. I thought the program would just give me new skills, but it gave me so much more — a full set of tools and knowledge to launch new products or even start my own business."


Kirilo Beresnev, last year's graduate