If you are looking for a learning program to help you become a data engineer, your search can stop here. WeCloudData’s Data Engineering Bootcamp is the most comprehensive and effective program to help you achieve that goal.

Data Engineering programs aren’t easy to design because curriculums must be frequently updated due to the rapid changes in tools and platforms in the data landscape. Traditional university programs will not be able to keep it up to date. Data Engineering is also hard to teach because you need instructors with a strong industry background and hands-on experience. That’s why you don’t find many options out there.

At WeCloudData, we teach you essential skills for transitioning into a modern DE role and allow you to build your project portfolio. Most importantly, this program offers post-graduation job support, mentorship, and referrals to help you transition. So read along and learn why you should stop looking and enrol in the best data engineering program.

At a Glance

Advanced

What you will learn

You will learn modern data engineering skills and tools in the classroom, practice what you learn by working on real capstone projects to build up experience, and learn from your mentors during your job search.

Summary

Cutting-edge Skills

ETL/ELT, Data lake, Lakehouse, Real-time, Data pipelines

Project-based Learning

Build end-to-end data pipelines

One-on-one Support

4 students : 1 teacher

Career Support

Through every stage of search

Part-time

240 Hours

Online Live

24 Weeks

About the Program

The Applied Data Engineering Certificate Program is created to help new graduates, IT professionals, and career switchers break into data engineering. The learning package includes six months of training and job support after graduation. The part-time option is excellent for work professionals who want to keep their daytime job and commit to learning new skills on weekday evenings and during the weekends. The full-time option also comes with real client projects to help you quickly build up relevant experience.

This program is not created for the faint-hearted. Though it’s intense and requires big commitments, the learning outcome will be very rewarding!

POTENTIAL JOB TITLES

Data Engineer

Cloud Data Engineer

Data Warehouse Developer

Data Warehouse Engineer

Analytics Engineer

Big Data Developer

ETL Specialist

ETL Developer

Software Engineer (Data)

Data Architect

Data Integration Developer

Data Solution Developer

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WeCloudData is the perfect place to grow your career

Choose your network & mentor wisely

Interacting with expert instructors, engaging with classmates, working on group projects, meeting with real clients and networking with a community of like-minded professionals. You'll be able to build your network and collaborate with people from all backgrounds, strengthening bonds and making friends in the process!

Solving real-world problems

In our bootcamp, we'll give you an opportunity that many graduates don't have: work on something meaningful and important right away. You will be able to even contribute ideas or solutions that make an impactful change! Teamwork is an essential part of data career. In our bootcamp, we'll have you work with other students and a Project Manager to complete a Real-Client project.

Comprehensive bootcamp with a focus on skills that are in high demand

No other bootcamp offers the flexibility and variety of topics, the number of hours and instructors, and the depth of knowledge in this industry. WeCloudData is a one-stop destination to learn data science - from basic concepts to building data-driven applications. Your learning is personalized and all your questions are answered by our expert instructors.

Ranked #1 Data Training Program

 4.9/5

 4.96/5

 4.95/5

A path more than just courses

BOOTCAMP

Learn cutting-edge skills from expert instructors

PROJECT

Gain hands-on experience with Real-client Project

career

Get 1-on-1 mentorship from our professionals

Portfolio Projects

Gain Hands-on Experience with Real-client Projects

One of the best ways to get the experience needed for a data science career is to start with a project. WeCloudData is one of the few companies who offers this opportunity. In our bootcamp, we’ll give you an opportunity that many graduates don’t have: work on something meaningful and important right away. You will be able to even contribute ideas or solutions that make an impactful change!

CLIENT

Entertainment

project

Modern Data Warehouse for Collector Cars Business

Implement an Azure-based data warehouse in the cloud. Ingested data using Azure Data Factory, implemented ELT pipelines using dbt and Synapse Analytics, created proof of concepts dashboards using PowerBI.

CLIENT

Agriculture Tech Startup

project

Real-time Analytics Pipeline on AWS

Our students helped an agriculture tech startup deploy a real-time sensor data monitoring tool on AWS. The project The models allow the client to have real-time insights about the sensor data collected from the IoT platform.

Portfolio Project

Build real project experience to differentiate

We also have a capstone project that gives our students the chance to synthesize their learning and build a portfolio piece they can showcase on their resume or LinkedIn profile. This helps them stand out from other applicants when applying for jobs or opportunities.

LEARNING EXPERIENCE

Drive Success with Interactive Learning Experience

Interact with faculty >

Interact with classmates >

Interact with community >

Interact with client >

Interact with mentors >

Interact with faculty >

Interact with classmates >

Interact with community >

Interact with client >

Interact with mentors >

FACULTY TEAM

Learn from the best

We’ve brought together a team of highly skilled and experienced instructors to help you learn effectively. Our instructors have a passion for teaching and a wealth of real-world experiences in their respective fields, so you can be confident that you’re learning from the best.

Stan Taov

Data Engineer @ Telus

Stan Taov is a professional data engineer with hands-on experience in building, validating and deploying machine learning models and creating end-to-end data pipelines. He is passionate about all things data. Stan has strong knowledge of converting business problems into analytical use cases and enjoys solving problems and building data-driven architecture. Stan has a passion for big data technologies and machine learning. Stan finished the Applied Data Engineering diploma program from WeCloudData and York University’s machine learning and predictive analytics certification programs. Stan switched his career multiple times, he moved from civil engineering to business and marketing and from the business field, he moved to data engineering. Currently, Stan works for Telus where he foresees and solves any operational issues with the on-prem cluster. He builds ETL pipelines and deploys spark analytical workloads.

Indrani Gorti

Director of Platform and ML engineering, Loblaw Digital

Indrani Gorti is a polyglot with experience in data engineering, data science, and solving business problems using ML and AI. She has worked in major industries like Finance, Telecommunications, Technology, Retail, and Startups. Her work has involved end-to-end projects from data ingestion, data analysis to the deployment of models in various setups using user transaction and interaction logs. Indrani is a Director of Platform and ML engineering at Loblaw Digital. She holds a BS and MS in Computer Science.

Zheng Xu

Data Engineer, The Globe and Mail

Zheng is currently a data engineer at one of the largest Canadian newspaper company where he builds and supports the data application from other teams in the company. He specializes in building data pipelines using Apache Airflow, data integration and ETL/ELT in Snowflake/Redshift, and developing big data applications using Apache Spark on Databricks. He teaches with WeCloudData in the Data Engineering program as an assistant instructor. Topics he covers include Airflow, Cassandra, Spark, and Spark Streaming.

Edwin Guo

Big Data Specialist @ CPPIB

Edwin is an expert Data Engineer and Cloud Architect who is specialized in Distributed Computing, Distributed Storage, Microservice, Cloud(AWS), Machine learning and Blockchain technologies. Skilled in Spark, Apache Kafka, Akka, Cassandra and various popular tools in the open-source landscape, he has had the opportunity to lead many challenging big data projects in the past. Coming from a Software Engineer background with a strong passion for the CS space, Edwin Guo is well versed in productive languages such as Scala, Java, Clojure, Python, and Golang. His past experience covers many domains including telecommunications, stock market price dissemination/portfolio management system, customer loyalty programs, and cybersecurity.

CURRICULUM

Be ready for the new economy

WeCloudData Bootcamps are designed to be project-based. We not only cover essential theories, but also teach how to apply tools and platforms that are in high demand today. Our program curriculum is also highly adaptive to the latest market trends.

Module 1

Linux and Docker

This module teaches students the fundamentals of Linux operating systems and containerization. We will train students to have decent enough command line skills so that they can work with containers, automation, and cloud CLIs. It equips students with the necessary skills to be able to work on big data, cloud computing, and data pipeline automation related projects.

LEARNING OUTCOMES

Become familiar with linux operating systems
Write bash/shell scripts to automate repetitive tasks
Create, build, and deploy docker containers and images
Run applications in a docker container
Deploy applications using docker compose
Work on a small yet complex project to apply what’s covered in this module

Key Skill:

Linux Commands, Shell Scripting, Docker Commands, Docker File, Docker Compose, Flask Application

Tools:

Ubuntu

VsCode

VMBox

Docker

Tools:

Python

AWS-S3

AWS-EC2

Lambda

Serverless

Docker

Module 2

Python for Data Engineering

Python is one of the core skills of a data engineer and is highly popular in the job market. In this module, students will learn how to use Python for different data engineering tasks and utilize Python to interact with Cloud Containers, Servers, and Serverless tools. You will also learn to use several AWS services including EC2, S3, Lambda, and IAM.

LEARNING OUTCOMES

Use different Python libraries for various data engineering use cases
Build and deploy Python applications on Cloud instances
Deploy Serverless applications using Python for AWS Lambda
Complete two mini-projects to improve Python and AWS skills

Key Skill:

Python , AWS EC2, AWS S3, AWS Lambda, Docker, Python OOP, Python Logging

Module 3

Modern Data Stack

Data warehouse is a popular data engineering infrastructure in most companies. This module focuses on teaching students the modern data stack: Airbyte, Snowflake, dbt, and Reverse ETL. Students will learn how to work with modern data warehouse such as Snowflake and Amazon Redshift, create data models, and use dbt to orchestrate SQL-based ELT transformation pipelines.

LEARNING OUTCOMES

Learn the internals of relational databases (RDBMS)
Build data models and work with modern data warehouses such as Snowflake and Redshift
Understand data connectors and ingestion tools such as Fivetran and Airbyte
Write dbt SQL workflows to transform data in data warehouse
Understand the basics of reverse ETL and different business use cases
Complete two mini-projects

Key Skill:

ELT, ETL, Reverse ETL, Data Connectors, Data Modelling, Data Warehouse, Dimensional Modeling, OBT (One-Big-Table), Wide Tables, Snowflake, Redshift, Apache Airbyte

Tools:

Snowflake

Redshift

DBT

Fivetran

Hightouch

Postgres

Tools:

Databricks

EMR

Spark

Glue

Module 4

Big Data and Data Lake

In this module, students will learn to work with big data technologies such as Apache Spark and Hadoop. Data Lake concept will be introduced so students understand the different use case scenarios of big data storage. Students then learn how to develop Spark applications to process big data. Spark jobs will be deployed in local mode, in AWS EMR, as well as Databricks platform. This module will go in-depth about Spark internals and Spark job optimizations.

LEARNING OUTCOMES

Learn the principles of big data and distributed systems
Understand the pros and cons of Data Lake vs Data Warehouse
Learn different use cases of Data Lake and how to set up staging, processed, and production zones
Develop Spark ETL scripts and submit jobs to Databricks and AWS EMR
Deploy Serverless Spark jobs to AWS Glue
Process big data using federated queries services such as Athen and Preto
Complete three mini-projects to showcase your end-to-end big data processing skills

Key Skill:

PySpark, Spark Optimization, EMR, MapReduce, Hadoop, Hive, Presto, Athena, Databricks, Spark Job Tuning, Data Lake

Module 5

Build Data Pipelines

In this Module, students will learn how to build and deploy end-to-end a data pipelines for data integration and ETL. We will introduce the most popular ways of building dataflows and compare different popular tools.

LEARNING OUTCOMES

Deploy and configure Apache Airflow in production environment
Get familiar with managed Airflow services on AWS
Develop Airflow DAGs (Direct Acyclic Graph) and set up dependencies among different operators
Orchestrate end-to-end data pipelines using Airflow and run complex ETL jobs
Understand the current landscape of data pipelining and orchestration.
Understand the pros and cons of Airflow compared to Dagster and Prefect.
Learn how to orchestrate Serverless dataflows using AWS Lambda and Step Functions

Key Skill:

Airflow Deployment, Data Pipelines, Pipeline Orchestration, Data Automation, AWS Lambda, AWS Step Function, Perfect, Dagster

Tools:

Airflow

Dagster

Prefect

StepFunc

Lambda

Tools:

DynamoDB

Elastic

Elasticsearch

Logstash

Kibana

Module 6

NoSQL Database

In this module, students will learn how to work with NoSQL databases. We will help students understand the CAP theorem and motivation behind NoSQL databases. Since there are many NoSQL database engines, we choose to focus on DynamoDB and Elasticsearch.

LEARNING OUTCOMES

Understand the CAP theorem
Understand the NoSQL use cases
Survey the NoSQL database landscape
Learn how to do data modelling in DynamoDB and Elasticseach
Learn how to ingest data into NoSQL databases
Understand log file ingestion and log file analysis with Elasticsearch and the ELK stack
Learn how to scale applications using DynamoDB

Key Skill:

CAP Theorem, NoSQL, DynamoDB, Elasticsearch , ELK, Log Analysis, Data Modelling

Module 7

Data Lakehouse and Streaming

A data lakehouse is a data architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. In this module, students will learn how to set up Change Data Capture (CDC), data ingestion, Kafka, Apache Hudi/Iceberg, and Spark Streaming.

LEARNING OUTCOMES

Set up CDC using Debezium
Set up Hudi or Iceberg on AWS EMR
Ingest data into Apache Kafka
Manage upserts with Apache Hudi/Iceberg
Working with streaming data using Spark Streaming
Complete an end-to-end Data Lakehouse project

Key Skill:

Spark Streaming, Data Lakehouse, Upserts, Change Data Capture, CDC, Debezium, Apache Spark, Apache Flink, Apache Kafka, Streaming Data Processing, Real-time Data

Tools:

Nifi

Kafka

Hudi

Iceberg

Debezium

Flink

Spark

Tools:

Leetcode

Hackerrank

Module 8

Career Preparation

Before entering the 1-1 career mentoring, students will learn about the Data Science job market and build job search skills. Career coaches will teach graduates how to structure resumes, apply for jobs, and ace the interviews. Students work in groups for peer mock interview practice.

LEARNING OUTCOMES

Career services included in the bootcamp include

Resume workshops
Group interview practice
Portfolio project mentoring
Coding interview practice and additional resources (Leetcode/hackerrank)
Peer programming practice and code reviews

Career services included after graduation (6 months)

One-on-one career mentoring sessions with data scientists for 6 months after graduation
One-on-one resume critique
One-on-one mock interview sessions with data science mentors
Job referrals and networking sessions

Key Skill:

Research, Leetcode, System Design, Networking, Salary Negotiation

SCHEDULE

Upcoming Start Dates

US Online

Toronto

Vancouver

US Online

Toronto

Vancouver

Career Services

Career success takes more than just courses

Taking courses alone don’t guarantee career success. WeCloudData’s career mentoring service, community events, and workshops are top-notch! We put in lots of effort outside of the classes to help learners grow their knowledge, confidence, job skills as well as network.

1-on-1 Mentorship

Available in all bootcamp programs, the career mentorship service helps close job market knowledge gap and provides the support our learners need to land a job.

Networking & Community

WeCloudOpen is a community built for tech leaners, practitioners who want to share thoughts, tips, and best practices with fellow learners and grow together.

Events & Workshops

Catching up with the latest tech industry trends by attending WeCloudOpen Workshops and community events. Learn practical tools and always stay relevant.

OUR ALUMNI ARE WORKING AT

student success

What our graduates are saying

Laura Vieira

Graduated 2021 | Reviewed on 17 October 2021

“Amazing course and support”

The course was really great a little too fast if you are not in a technical field already. You will need to study hard reviewing classes and making the labs and assignments but you always have the support of the TAs (they are awesome) or even the instructors and your own classmates that are always helping each other via Slack. There will be a final project where you will need to present a pipeline that you created (don’t worry they will be helping you!). Then, they will be helping you to find a job. Shaohua is always looking for the best for his students, he wants to make sure that you have the best experience with them.

 5/5

Albert N.

Graduated 2022 | Overall ⭐⭐⭐⭐⭐

“A solid bootcamp”

I completed the Data Engineering bootcamp at Weclouddata and was fortunate to land a job approximately 1 month after graduating. As many others have mentioned, the most significant reason that makes WCD stand out is its corporate partnerships. These companies, ranging from high profile multinationals to small local startups, provide real development work for the students and in turn makes all the difference on your resume. As long as you work hard in this program, you have a good chance of success.

 5/5

Anonymous

Graduated 2022 | Overall ⭐⭐⭐⭐⭐

“Data Engineering boot camp – great experience”

Prior to joining the WeCloudData Data Engineering boot camp I already had some Data Engineering experience in previous jobs and a master’s degree in big data and machine learning. This program provided me with the opportunity to enhance my data engineering background and helped me land a Senior Data Engineer role in AI operations.

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Want more details about this program? Unsure about which path to take? Apply now to reserve a spot or make an appointment with our learning advisor.

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Join WeCloud Open and start learning today! We provide open courses, career guide, and learning resources. It’s a great way to start your career in tech!

FAQ

Frequently asked questions about the bootcamp

What makes WeCloudData different/better?

WeCloudData provides an end-to-end solution for career switchers. With WeCloudData, students expect to follow a well-structured curriculum, get on-demand and classroom-based support when they need it, work on real-world problem solving, and get 1<>1 career mentorship from real experts.

What if I miss a few sessions?

All online lectures are recorded so the students can watch them in case he/she misses a few lessons. You can also book on-demand TA sessions with our TAs to help you catch up on the material.

Do you offer real-industry projects?

Yes, the nature of our training is hands-on. Students work on end-to-end projects and business use cases to build an amazing portfolio!

Do you offer financial support?

We offer the following financial aids in US and Canada: scholarship, loan, and payment plans. Government grant such as BJO is also available in Canada.

What cloud platforms are covered? Can we learn an additional one?

The cloud platform this course focuses on is AWS. We don’t teach other cloud providers, but we will provide self-paced Microsoft Azure/GCP materials for students in the immersive program.

How much time is required to spend on projects and assignments to expect the best result?

Typically, students must assign at least 15-20 hours per week (including lectures) to expect good results.

How much machine learning is involved?

Data engineers don’t need to have extensive knowledge of machine learning. However, data engineers work closely with data scientists and analysts. Understanding the high-level DS/ML workflow will be very useful. WeCloudData provides Open Courses that allow data engineers to learn more about data science and machine learning.

What’re the prerequisites for joining the data engineering bootcamp?

SQL and Python experience will be definitely useful. We have admission assessments that help us decide whether a student meets the admission criteria right away. For students who don’t meet the admission criteria, we would recommend going through the pre-bootcamp learning. Ideally, 2-3 months of self-paced learning is required to build up the foundational SQL and Python skills.

What are the lab activities? Is attendance mandatory?

We encourage students to attend all the labs, but it is not mandatory. Students will finish a mini project during the labs by following the live instructions provided by teaching assistants. Students can watch the lab recordings if they missed it.

How many projects are offered and what are those?

Students will complete two big end-to-end projects during the bootcamp. The two projects are very comprehensive and help students put things they learn in the bootcamp together. System design is required and students will need to implement everything from scratch. Students will also implement 13 mini-projects during the lab sessions.

How many projects can I complete and add to my portfolio?

Two large-scope portfolio projects and 13 mini-projects.

I have years of IT experience, is it possible to get a senior data engineer job after graduation?

Yes, it’s possible! Your past IT experience is valuable and with the right preparation and kick-ass portfolio projects, we’ve seen students getting hired into senior roles.

WeCloudData is the leading data science and AI academy. Our blended learning courses have helped thousands of learners and many enterprises make successful leaps in their data journeys.

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