Data Engineering Bootcamp (Self-paced)

Combine self-paced materials with mentor sessions for a comprehensive and flexible learning experience

Your search for a comprehensive self-paced learning program to become a data engineer ends here with WeCloudData’s Data Engineering Bootcamp. Crafting effective Data Engineering programs is challenging due to the evolving nature of tools and platforms in the data landscape, a task traditional university programs may struggle to keep up with. At WeCloudData, our industry-seasoned instructors provide hands-on experience, teaching essential skills for a seamless transition into a modern Data Engineering role. The program emphasizes building a robust project portfolio and stands out with post-graduation job support, mentorship, and referrals to facilitate a smooth transition. Enroll now and discover why WeCloudData is the best choice for your data engineering journey.

Explore our Program Package to find:

Access our comprehensive ✨self-paced✨ learning materials 24/7

Learn on your own terms and schedule. Our self-paced approach allows you to delve into the world of data without the pressure of deadlines. Take control of your learning journey, progressing at a pace that suits your lifestyle.

Learn Anytime, Anywhere

Learn at your own pace without deadlines, tailoring your journey to fit your lifestyle.

Interactive Modules

Dive deep into data concepts through videos, quizzes, and hands-on exercises that bring theory to life.

TA Support

Get dedicated support from experienced teaching assistants for guidance whenever needed.

Real-World Applications

Our course content is rooted in practical, industry-relevant scenarios, providing insights directly applicable to your professional endeavors


About the Program

The Applied Data Engineering Certificate Program has been tailored for new graduates, IT professionals, and career switchers aiming to enter the dynamic field of data engineering. Our self-paced learning option provides flexibility for individuals to acquire new skills at their own pace, supported by on-demand TA, weekly mentoring sessions, and interactive review workshops. This program is designed to accommodate the schedules of working professionals, allowing you to balance learning with your existing job commitments during weekdays and weekends. Unlike the full-time program, the self-paced option empowers you to progress at your convenience, and real client projects are available to help you gain practical experience. While this self-paced journey demands dedication, the learning outcomes promise to be exceptionally rewarding!

What you will get
Top data bootcamp voted by students and partners

A Seamless and Enriching Learning Experience

Start Learning Anytime

Engage with self-paced materials designed for learning anytime, anywhere, and at your own pace.

Get TA Support

Teaching Assistants (TAs) are readily available on Slack to assist you with any questions during the bootcamp.

Review Session

Participate in live, interactive workshops with instructors for dynamic review and reinforcement of the covered materials in each module.


Personalized Mentorship

Book a weekly meeting with a mentor who will guide you through your learning and career journey, providing personalized support.


Explore Our Comprehensive Curriculum

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. 

  • Linux and Docker
    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.
    • 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
    • Linux Commands
    • Shell Scripting
    • Docker Commands
    • Docker File
    • Docker Compose
    • Flask Application
  • Python for Data Engineering
    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.
    • 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
    • Python
    • AWS EC2
    • AWS S3
    • AWS Lambda
    • Docker
    • Python OOP
    • Python Logging
  • Modern Data Stack
    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.
    • 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 
    • ELT
    • ETL
    • Reverse ETL
    • Data Connectors
    • Data Modelling
    • Data Warehouse
    • Dimensional Modeling
    • OBT (One-Big-Table)
    • Wide Tables
    • Snowflake
    • Redshift
    • Apache Airbyte
  • Big Data and Data Lake
    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.
    • 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
    • PySpark
    • Spark Optimization
    • EMR
    • MapReduce
    • Hadoop
    • Hive
    • Presto
    • Athena
    • Databricks
    • Spark Job Tuning
    • Data Lake
  • Build Data Pipelines
    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.
    • 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
    • Airflow Deployment
    • Data Pipelines
    • Pipeline Orchestration
    • Data Automation
    • AWS Lambda
    • AWS Step Function
    • Perfect
    • Dagster
  • NoSQL Database
    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.
    • 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
    • CAP Theorem
    • NoSQL
    • DynamoDB
    • Elasticsearch
    • ELK
    • Log Analysis
    • Data Modelling
  • Data Lakehouse and Streaming
    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.
    • 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
    • Spark Streaming
    • Data Lakehouse
    • Upserts
    • Change Data Capture
    • CDC
    • Debezium
    • Apache Spark
    • Apache Flink
    • Apache Kafka
    • Streaming Data Processing
    • Real-time Data
  • Career Preparation
    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.

    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
    • Research
    • Leetcode
    • System Design
    • Networking
    • Salary Negotiation

Nail your job search journey via 1-on-1 mentoring

From the beginning of your self-paced bootcamp, our experienced mentors are here to guide you every step of the way. Have questions about the materials? Need career advice to navigate your chosen field? Your dedicated mentor is ready to provide insights, support, and valuable guidance. Together, we’ll shape your learning experience and pave the way for your successful career

Tailored Acceleration and Support:

Your mentor is there to address questions promptly, ensuring a tailored and efficient learning journey

Enhanced Motivation:

Stay motivated and engaged with your studies as your mentor provides encouragement, feedback, and a supportive presence throughout your self-paced bootcamp

Industry Insights:

Gain valuable career advice, insights, and industry knowledge from your mentor, enhancing your understanding and preparing you for success in your chosen field.

Real Client Projects

Gain Hands-on Experience with Real-client Projects ✨

One of the best ways to get the experience needed for a data & tech 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!

*Please note that the Real Client Project is now optional and not included in the Self-paced bootcamp tuition.

Interested in Real Client Project?
Portfolio Projects

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.


Tuition and Scholarship

Standard Package:

4,000 USD

Self-paced materials + 30-hour 1-on-1 mentor support
Extensive Package:

6,000 USD

Self-paced materials + 30-hour 1-on-1 mentor support + 6-month career service

We believe in investing in the future of our industry and supporting individuals in their professional journeys. That’s why WeCloudData is proud to offer scholarships for individuals looking to pursue professional development or make a career change. 

The Women in Tech scholarship supports and empowers women pursuing careers in the technology industry. This scholarship aims to address gender diversity and underrepresentation in tech by providing financial assistance, mentorship, and access to our comprehensive bootcamp. We celebrate the achievements of aspiring women technologists and equip them with the skills to thrive in the tech sector.

The Laid-off Support is a special offering designed to provide financial assistance and support to individuals who have recently been laid off from their jobs. We understand the challenges and uncertainties that come with job loss, and we want to help those affected continue their professional development in the technology sector. This provides reduced pricing and access to our comprehensive range of courses, allowing laid-off individuals to acquire new skills, enhance their knowledge, and increase their chances of finding new opportunities in the competitive job market.

The Fresh Grads Scholarship is a scholarship program that offers financial assistance to outstanding individuals who have recently completed their undergraduate or postgraduate studies within 12 months and are looking to kickstart their careers in data and tech. The scholarship aims to bridge the gap between academia and industry, empowering fresh graduates to become competent data professionals through an intensive and comprehensive bootcamp.

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.

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.


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.

Let WeCloud Accelerate Your Career in Tech

Start your career today!

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. 


Frequently asked questions about the bootcamp
Data engineers help the organization ingest, collection, and transform large amounts of data. Data engineers deal with raw data and understands data models very well. The output of DE’s work are usually data warehouse or data lakes that store cleansed and transformed data. Data scientists and analysts will consume those data for business intelligence and machine learning/predictive analytics. Data analysts will focus on analyzing data to address ad-hoc business questions. They are good at SQL and database queries and know the business metrics well. Data analysts will also build KPI dashboards that are consumed by business teams and executives for day to day operations. Data scientists perform advanced analytics and machine learning to help the business address predictive questions. It goes beyond answering the what and why questions, and help business make personalized recommendations to improve sales, identifying high-risk transactions to prevent loss, finding good customer segments to generate more revenue, etc.
First of all, WCD’s data engineer bootcamp covers the latest tech stacks that are extremely relevant in the job market. WeCloudData also offers a unique project-based learning approach. Unlike other bootcamps, we give students the opportunity to work on real-life consulting projects as part of the learning journey. The real projects help students gain confidence, show real experience on the resume, get more interviews, have real experience to talk about during the interviews, and adapt to new jobs quickly.
Learners are expected to join the program with solid Python and SQL skills. The DE bootcamp is not an entry level course that teaches learners basic programming from scratch. If you don’t meet the pre-requisites, we recommend you go through the Data fundamentals course to get prepared. Going through the pre-bootcamp will make sure you can comprehend most of the new materials taught in this program quickly, which will leave you more time to focus on practice instead of struggling with the basics.
We’ve seen a good mix of learners from various background. About 30% of the learners are coming from non-tech and non-coding background. These learners typically join the pre-bootcamp and complete data fundamentals course to develop the fundamental skills first. This helps them succeed in the DE bootcamp. About 70% learners come from IT, software, and data background. Typically learner profiles include: 1. data scientist who want to gain DE skills or switch to data engineering. 2. Software engineers who want to become a data engineer. 3. IT professionals in security, QA, database administration (DBAs). 4. Data engineers from traditional data tech stack background such as ETL developers and data warehouse engineers 4. New graduates from computer science or computer engineering programs. 5. Non-tech background learners who have completed WeCloudData’s data fundamentals short courses as a pre-requisites
To get the most up to date information about the data engineer job market, we recommend you check out the Job Market Report and blog posts on our website. Typically, data engineers are expected to be paid an average base salary of $100k CAD in Canada and $120k USD in the U.S.. Senior data engineers can be compensated well over $150k USD.
Data engineer job market is booming. The demand is increasing and currently the supply of data engineers with relevant skills is low. So it’s a great time to become a data engineer. However, data engineer jobs have high entry bars. The successful candidates are expected to have 3+ years of experience. If you’re new to this field or switching career, the experience gap can be closed by working on real client projects via WeCloudData’s bootcamp. It’s not as competitive as other data fields such as data analytics and data science because there’re less qualified job applicants who have the right skills.
Computer science is not a hard requirement though it would be preferred. About 80% of the DE jobs only require a bachelor’s degree.
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.
Software engineering knowledge is not necessary but definitely helpful. Many students have successfully completed the course without a CS background. We highly recommend learners pick up some basic CS knowledge before attending this course.
The cloud platform this course focuses on is AWS and Azure. The bootcamp contains 3 courses. 2 of them teaches AWS and the other one covers Azure. We will also provide self-paced GCP materials for students in the immersive program.
There are 3 main courses in the DE Bootcamp: analytics engineering, big data engineering, and data lakehouse engineering. These courses can be taken as individual short courses. You get a much better deal by taking the Bootcamp which includes not only all 3 courses but also the career service.
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.
We encourage students to attend all lab sessions, 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.
Students will complete three big end-to-end projects during the bootcamp. The three capstone 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 10 mini-projects during the lab sessions.
It won’t be easy. If you read some of our alumni’s reviews you will know that some of them put in significant amount of effort. The journey may not be smooth because there are a lot of new information to take in on a weekly basis and you need to keep studying hard for 6 months. It might be overwhelming and even frustrating from time to time but the reward is real! Students who successfully complete the program all feel a great sense of achievement and almost always proud of what they were able to accomplish in 6 months. The payoff is real because many students moved on to DE jobs and gained so much confidence in themselves. If you do get behind, WeCloud allows students to re-take a course for free. We are trying to be as flexible as possible for our learners.
We firmly believe that tools like ChatGPT will only make data scientists and engineers more efficient. Data engineering is also probably the hardest among all data jobs to be replaced in the near future. Because data engineers usually deal with large amount of raw data directly and without knowing a company’s private data, generative AI can’t generate any meaningful data transformation guide. We can use prompting engineering to save time on coding but it still requires human who understands the business rules and data context to make decisions on how to architect and engineer data systems. Data engineering demand will increase as the digital world gets more automated.
You don’t need a data engineering certificate to get a DE job. As a matter of fact, certification is not very popular in the field of data engineering because assessing data engineers require very hands-on approach and most certification exams are multiple choice question based so it doesn’t have much credibility. There’re a few that’s worth considering including AWS associate cloud architect certificate and Databricks spark certification. Among all online courses, bootcamps, and university programs, WeCloudData’s data engineer bootcamp certificate definitely provides the highest value.
This course is designed to be very hands-on. It’s impossible to become good at data engineering without getting hands dirty and building data pipelines. Be prepared to roll up your sleeve and enjoy the bumpy ride. There will be a lot of challenges waiting for you to tackle.
Depending on your existing skill sets and experience with SQL, Python, and linux, learners usually spend 15 to 20 hours each week (including the lectures and labs)
Yes, during the regular weeks we have office hours and labs sheets students get to follow labs and ask questions. During the project weeks, students will join the project mentoring sessions to interact the project mentors.
There are two types of projects: personal projects (also called capstone or portfolio projects) and real client projects. All students in the course will need to complete the capstone project. The real client project is a different training and career service offered at WeCloudData via our partner Beamdata. Learners will become a trainee and receive project-based training. Learners will be assigned to a real project team to work with clients and get mentored and trained by our project managers and project leads. It’s a great learning opportunity and also allow the students to gain real experience to stand out in the job market. You can talk to our learning advisors to find more details.
Yes. The Data Engineering Bootcamp comes with 6 months of career mentorship. During the bootcamp, we host resume workshops, interview preparation sessions and help students with their resumes and portfolio projects. After the Bootcamp, students will enter a 6-month career mentoring phase where they work with an industry mentor on a one-on-one basis for job search. Mentoring sessions are one of the most important advantages of WeCloudData’s bootcamps. It offers services beyond resume help and the mentors are all data industry professionals instead of regular career counselors.
Our career services include: resume workshop, interview workshop, industry guest lectures, job recommendation and referral, 1-1 career mentoring.
You can find our alumni reviews and stories by visiting the student success pages.
Yes. If you’re doing the bootcamp to up-skill yourself you can opt out of the career service. Fees can be deducted from the tuition.
Upon successfully completing the Bootcamp, Canadian learners will get a diploma issued by WeCloudData Academy (under Ministry of Education). Please contact our learning advisor for more details. For US and international learners, you will get a Bootcamp certificate.
Yes. Scholarship is available for students who meet the requirements. A scholarship test needs to be completed and the learner needs have a 20-minute live assessment with the program manager. Alumni who have completed courses that meet the pre-requisites will also be eligible for scholarships.
Yes. We offer flexible payment plans and work with 3rd parties to offer loans as well. Please fill out the inquiry form to access the course package page. It has the payment plan details. Or you can contact our learning advisors for more details.
View our Data Engineering Bootcamp (Self-paced) course package


Data Engineering Bootcamp (Self-paced)

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View our Data Engineering Bootcamp (Self-paced) course package