JOIN ONE OF THE MOST IN-DEMAND PROFESSION IN IT WORLD
$35.20 Billion
Market Worth by 2027
190,000 to 400,000
More Job Openings by 2027
60 to 75%
Growth by 2027
$105,000
Median Salary
ABOUT THIS COURSE
Big Data Engineers are the backbone of the management of large volumes of data. They’re tasked with designing and developing solutions for large scale cluster data processing. The Big Data Engineer skill plan will help you extract value from large, messy, unstructured, and complex data whilst teaching you the fundamentals of big data frameworks such as Hadoop and Spark.
Gathered together from the experience of real world Big Data engineers at innovative companies, this Skill Plan will teach you the vital skills needed to excel as a Big Data Engineer today.
Intern Program
When you graduate, you could work remotely as a freelancer or as a full-staff at GreaterHeight Academy for up to 3–4 months as a paid intern.
Certificates
The course is a package of more than 50 hours of instructor-led training and 100+ hours of hand-on. Once you meet the requirements of the program, you will receive Greaterheight Academy's certificate stating that you have acquired the skillset of a Big Data Engineer.
1-on-1 Mentorship
You will get one-on-one help from our mentor(s) and student instructors who will be in charge of reviewing your codes and all of your exercises and project assignments at Greaterheight Academy.
Develop Your Skill
Become a Big Data Engineer and learn data science basics, manipulate data and discover Skill Plan that will teach you the vital skills needed to excel as a Big Data Engineer today.
Who Should Attend This Course
Being a Big Data Engineer is the perfect amalgam of experience, data science knowledge, and the correct tools/technologies. It is a good career choice for both newbies and experienced professionals who have industry knowledge. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue this path. We would recommend this path strongly for professionals in the following roles:
- IT, Banking and Finance professionals, governments etc.
- Marketing and Supply-Chain-Network Managers
- Freshers into data analytics domain AND Students in UG/ PG Analytics Programs
CAREER SUPPORT
We provide each of our Big Data Engineer graduates with access to job readiness training, connections to employers and opportunity to hone new skills.
Job Preparation
Build a strong resume with one-on-one coaching support. Learn how to present your code and discuss open source contributions.
Career Resources
Visit development teams at local companies. Attend panel discussions with industry experts.
Networking Opportunities
Showcase your work to potential employers in our global network. Get to know members of your local tech community.
STUDENT LIFE
We break up our daily schedule with a mix of presentations, interactive labs and project collaboration, no two days look exactly alike, but here's an example of what your day could look like on campus.
9
am
Review
Group Review
Daily review and code exercises that reinforce concepts and activities
10
am
Class
Instructor-guided Lessons & Activities
Learn key objectives through lectures, discussions, and activities
12
noon
Lunch
Panel Discussion
Hear from industry insiders during talks and panel discussions (recurring)(Optional)
2
pm
Labs & Exercises
Student-guided Group Activities
Practice new skills, work on labs solo or in groups, & receive instructions on key topics.
5
pm
One-on-Ones
Catch-up on Goals & Progess
Personal review and support from instructors
6
pm
Homework
Panel Discussion
Evening TAs are on hand to support the class in completing daily assignment and review exercises
Career Services
Our experienced team works directly with each student to ensure they are able to excel in their career search and negotiate multiple offers.
Online Presence
By graduation, you will have a strong, unique Big Data Engineer Programming portfolio, online profiles and a resume that reflects your value in the job market.
98%
Graduate Hiring Guaranteed
N150,000+
Avg Graduate Salary
50+
Partners & Collaborators
Online Presence
Our instructional staff conducts mock interviews, training exercises and role-play sessions designed to help you tackle the job interview.
WHAT YOU WLL LEARN
Gain the skills you need to land as a Big Data Engineer. GreaterHeight Academy teaches the in-demand skills you need to become a Big Data Engineer in just 4 to 6 months, and you will learn the following from fundamentals through advance, depending on your receptiveness to teaching and mentoring:
Hadoop Basics
The volume of data that is made publicly available is increasing every year. Success now and in the future will be measured by an individual’s ability to extract value from large data sets. The larger the data, the more difficult it becomes to manage the types of data collected, that is, it will be messy, unstructured, and complex. Starting with the fundamentals, this Skill Card gets you started with Hadoop and helps develop your skills when tackling and working with big data problems.
What will I be able to do?
Use the unique features of Hadoop 2 to model and analyze, Go beyond MapReduce and process data in real time with Spark, Build data processing flows using Apache Pig, Understand the fundamentals of HBase and get to grips with the HBase data model, and Manage big data clusters efficiently using the YARN framework.
The Course includes:
Learning Hadoop 2
Learning HBase
Hadoop Development
Hadoop Development is all about introducing you to the main frameworks and libraries that work with and on top of Hadoop. In this Skill Card, you will learn about Apache Hive, Pig, and Zookeeper. This card helps you develop the skills to read, write, and process analytics using Pig Latin. Get up to speed with Hive’s query language and data warehousing. Finally, using ZooKeeper, learn to coordinate clusters and provide highly-available distributed services that simplify development processes.
What will I be able to do?
Use Pig in design patterns that enable data movement across platforms; Discover how to use Hive's definition language
to describe data; Discover steps to set up and get started with ZooKeeper in a development environment; Transform data
by using Hive sorting, ordering, and functions; and Use ZooKeeper to solve common distributed coordination tasks.
The Course includes:
Apache Hive Essentials
Apache ZooKeeper Essentials
Pig Design Patterns
Spark Fundamentals
Spark is an open source cluster computing system that is designed to process large datasets with high speed and ease of development. Spark was developed as a standalone platform that makes use of large scale data analysis in real time. In this card, learn about Spark’s in-memory analytics, which pretty much allows it to process data as fast as possible. Learn all about Spark’s Machine Learning Library and how you can run the Spark framework on top of Hadoop clusters.
What will I be able to do?
Query Spark with a SQL-like query syntax; Discover Spark stream processing via Flume, HDFS; Examine clustering and
classification using MLlib; Perform large-scale graph processing and analysis with GraphX; and Combine Spark with H20
and deep learning.
The Course includes:
Fast Data Processing with Spark
Real-time Analytics
Data is constantly growing and changing, and having the ability to process data in real time can help you make sense of constantly changing data and obtain targeted results. There are a number of open source frameworks and libraries that support real-time analytics. In this card, explore real-time technologies, learn how to work with data in Hadoop, and see how to process, analyze, and obtain results in real time.
What will I be able to do?
Develop use cases for processing and analyzing data in real time, Integrate Kafka with Hadoop and Storm, Perform
interactive and exploratory data analytics using Spark SQL, Work through practical challenges and use cases of real-time
analytics versus batch analytics, and Understand the internals of Kafka's design and learn about message compression.
The Course includes:
Real-Time Big Data Analytics
Learning Apache Kafka
MongoDB Basics
MongoDB is a document database, which means data is read as a whole document and is not restricted to rows and columns to be stored. There are countless benefits to this approach, mainly scaling and handling large sets of unstructured data quickly to generate meaningful results. MongoDB Basics helps you make the connection between the speed and scalability of values in databases. This Skill Card helps teach you to manage complex events processing, horizontal scaling, and high performance.
What will I be able to do?
Get to grips with the latest features of MongoDB 3; Take an in-depth look at the Mongo programming driver APIs; Install,
configure, and administer MongoDB sharded clusters and replica sets; Begin writing applications using MongoDB in the Java
and Python languages.
The Course includes:
MongoDB Practical
Cassandra Basics
Cassandra, a distributed database management system that is massively scalable, suitable for managing large amounts of structured, semi-structured, and unstructured data. Cassandra Basics helps you get started with one of the few database systems that can process and manage fault-tolerant data in real time, generate high performance, and maintain high availability. Learn all about the Cassandra’s Query Language, CQL3, and explore each concept with real-world examples.
What will I be able to do?
Design rich schemas that capture the relationships between different data types, Master the advanced features available
in Cassandra 2.0, Ensure data integrity with lightweight transactions and logged batches, Implement best practices for
data modeling and access, and Effortlessly handle concurrent updates with collection columns.
The Course includes:
Learning Apache Cassandra
Search and Indexing Fundamentals
In this Skill Card, learn about two of the most popular scalable search systems: Apache Solr and Elasticsearch. This card will explore Apache Solr: a ready-to-deploy, Lucene-based, open source search engine. Learn to scale across servers and carry out real-time queries across billions of documents. Furthermore, learn all about Elasticsearch: create search applications, learn about schema-free architecture, and see how to index and search unstructured data.
What will I be able to do?
Improve your Solr instance and Solr cluster performance; Acquire the skills needed to index your data in different
formats, forms, and sources; Understand Apache Lucene and Elasticsearch's design and architecture; Choose the
appropriate amount of shards and replicas for your deployment; and Apply your knowledge to create scalable, efficient,
and fault tolerant clusters.
The Course includes:
Solr Practical
Mastering ElasticSearch
Git Fundamentals
Git is a magic tool you can use that can reverse time, resurrect old versions of code, and allow all developers to work simultaneously on one code base. It’s one of the most important developer tools available today, and is used in all areas of software development—from web development to data science.
What will I be able to do?
Set up and get started with Git, Understand the Git workflow, and Manage your version histories.
The Course includes:
Mastering Git
Git Version Control
Download our full curriculum to see what we teach week-by-week!
APPRENTICESHIP
Beyond the classroom, the Apprenticeship emphasizes real-world work experience, collaboration with a team of developers, project planning and management, and pair programming, as well as interview and resume preparation. By building professional experience into the GreaterHeight Academy program, we ensure that our developers continue to grow after class-room interactions. Every day apprenticing makes you more competitive in the industry and more likely to land the Big Data Engineer position of your dreams.
GreaterHeight
Technologies
Our independent GreaterHeight Technologies, GreaterHeight Technologies, to provide GreaterHeight Academy graduates with the professional experience they need to launch their coding careers. Our developers deliver polished web applications to clients.
Work Alongside
Experienced Devs
During your Big Data Engineer apprenticeship, you'll pair program with the agency's more experienced Business Analyst. This opportunity allows apprentices to learn from senior devs hands-on, plus gain experience programming in pairs - a common industry practice.
Job Prep
Curriculum
Your apprenticeship with Greaterheight Academy also includes our three-part job-prep curriculum. You'll learn how to land interviews, improve the soft skills employers look for, and master Big Data Engineering Development and technical topics likely to come up in interviews.
BENEFITS
GUARANTEED
EXPERIENCE
Guaranteed way to gain real-world experience in your new profession and build an impressive Big Data Engineer Stack portfolio.
TEAM
COLLABORATION
Learn skills you can't get in a classroom: team collaboration, working with clients, agile, and more.
PROFESSIONAL
MENTORING
Gain knowledge from experienced professional developers throughout your apprenticeship.
SELF
CONFIDENCE
Gain confidence and prove to yourself that you are now a professional Big Data Engineer Stack developer.
TUITION
N550,000
Financing Available
Financing plans available through Greaterheight Academy and our hand-selectd financing partners, Skins Funds. Repayment period ranged from 0-5years with monthly payments as low as N20,000.00. Contact your Student Advisor for details.
We stand by your results
Get a job creating software upon graduation, or we will refund your tuition in full. See details
Payment Plans
Tuition can be paid upfront or over six installments. The installment plan: one payment of 50% of the program cost fee upon enrollment, and monthly installments of 10% until the Tuition is fully paid. We accept credit cards, debit cards, checks, and PayPal.
Scholarships
Diversity and Merit Based Scholarships available. Attend an info session to learn more.
Refund Policy
We'll provide you with a full refund if you drop out within 7 days of starting your course. If you choose to drop out later, you will receive a pro-rated refund based on the number of days you've spent in the program, minus a non-refundable 10% of program cost fee.
FUND YOUR FUTURE
Need payment assistant? or financing options allow you to focus on you goals instead of the barrier that stop you from reaching them.
Future Finance
Apply for fixed and term based merit loan
GET THE INFO FROM AN EXPERT
Dive deep into the curriculum, the course structure, and what you can achieve from a course mentor.
See if this program is a fit for you. Meet the GreaterHeight team, get an overview of the program curriculum, and chat with other students thinking about this program.
Become A Big Data Engineer information Session
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FAQs
We love questions, almost as much aswelove providing answers.Here are a few samplings of what we're typically asked, along with our responses.
At the end of this course you will create a project by developing Web Apps as you master the followings:
- Use the unique features of Hadoop 2 to model and analyze
- Go beyond MapReduce and process data in real time with Spark
- Build data processing flows using Apache Pig
- Understand the fundamentals of HBase and get to grips with the HBase data model
- Manage big data clusters efficiently using the YARN framework
- Use Pig in design patterns that enable data movement across platforms
- Discover how to use Hive's definition language to describe data
- Discover steps to set up and get started with ZooKeeper in a development environment
- Transform data by using Hive sorting, ordering, and functions
- Use ZooKeeper to solve common distributed coordination tasks
- Query Spark with a SQL-like query syntax
- Discover Spark stream processing via Flume, HDFS
- Examine clustering and classification using MLlib
- Perform large-scale graph processing and analysis with GraphX
- Combine Spark with H20 and deep learning
- Develop use cases for processing and analyzing data in real time
- Integrate Kafka with Hadoop and Storm
- Perform interactive and exploratory data analytics using Spark SQL
- Work through practical challenges and use cases of real-time analytics versus batch analytics
- Understand the internals of Kafka's design and learn about message compression
- Get to grips with the latest features of MongoDB 3
- Take an in-depth look at the Mongo programming driver APIs
- Install, configure, and administer MongoDB sharded clusters and replica sets
- Begin writing applications using MongoDB in the Java and Python languages
- Design rich schemas that capture the relationships between different data types
- Master the advanced features available in Cassandra 2.0
- Ensure data integrity with lightweight transactions and logged batches
- Implement best practices for data modeling and access
- Effortlessly handle concurrent updates with collection columns
- Improve your Solr instance and Solr cluster performance
- Acquire the skills needed to index your data in different formats, forms, and sources
- Understand Apache Lucene and Elasticsearch's design and architecture
- Choose the appropriate amount of shards and replicas for your deployment
- Apply your knowledge to create scalable, efficient, and fault tolerant clusters
View All FAQs
