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  • Industry-leading curriculum
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Become a data analyst through building hands-on data/business use cases

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Improve your data & AI skills through self-paced and instructor-led courses

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Learn to build impressive data/AI portfolio projects that get you hired

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Data Engineering

Data Engineering Bootcamp (West Coast)
Applied Data Engineering

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

Data Engineering programs aren’t easy to design because curriculums need to be frequently updated due to the rapid changes of 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 who have a strong industry background and hands-on experience. That’s why you don’t find many options out there.

At WeCloudData, we teach you the most essential skills required for transitioning into a modern DE role and give you opportunities to build up your project portfolio. Most importantly, this program offers post-graduation job support, mentorship, and job referrals to help you with the transition. Read along and learn why you should stop looking and get enrolled in the best data engineering program.

At a Glance
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.

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


24 weeks

Online Live

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 6 months of training and 6 months of job support after graduation. The part-time option is great for work professionals who want to keep their daytime job and commit to learning new skills on weekday evenings and during the weekends. Full-time option also comes with real client projects to help you build up your relevant experience fast.

This is NOT an easy program and requires a lot of commitment. But it’s also why it’s rewarding at the end. Learn more about Data Engineering career path.

Who should consider this diploma program?
  • Software engineers/developers who want to switch to the data engineering field
  • IT professionals from traditional ETL, database backgrounds who want to obtain the modern DE skills for career change
  • Current data scientists who want to work in data engineering
  • College graduates or anyone with the right mindset and dedication to become a data engineer
placement rate
student satisfaction
base salary
Our alumni are working at

What you will learn

Data engineers need to be strong coders. You need to be able to write production-grade code that can be tested and deployed in data pipelines. Python and SQL skills are prerequisites for the program. If you're still relatively new to programming, you can take advantage of the pre-Bootcamp learning support. As a data engineer, you need to know Linux command line, scala/python programming, and SQL. Understanding Object-Oriented Programming (OOP) and data structures is also a requirement. In 24 weeks, the students will go through regular coding challenges (weekly). At the end of the Bootcamp, through our Cracking the Coding Interview practice, you will be able to comfortably pass data engineering interview coding challenges.
  • Master SQL queries for data aggregation, complex joins, and advanced analytic functions (window function)
  • Master data structures and algorithms with Python
  • Learn the basics of functional programming with Scala (not expert level)
  • Get proficient with linux command lines and the basics of linux operating systems
  • Become skilled in version control with Github
  • Learn how to write testable code in Python and Scala
Most online courses will teach specific tools. But knowing 20+ tools doesn't mean you can solve real data problems. We strongly believe that problem-solving skills are the most essential for a successful career in data engineering. Therefore, we've designed a very unique approach to teaching learners how to solve tough problems and become independent thinkers.
  • Build a strong foundation in DE concepts and know the right questions to ask
  • Become a Google/Stackoverflow pro. Know the most relevant keywords to use for problem solving
  • Develop new skills in how to approach new projects and problems
  • Learn modern tools and platforms and know how to put them to work together
  • Become a better team player through group assignments, projects, and client projects
While docker and kubernetes are containerization and orchestration tools that DevOps engineers and infrastructure engineers will work on, data engineers also need to have a good understanding of it. Whether it's setting up airflow servers using docker compose, or running spark jobs on kubernetes, docker is an essential tool that data engineers need to be comfortable with.
  • Learn how docker containers work
  • Know how to deploy Flask apps using docker and docker compose
  • Understand the basics of kubernetes and container orchestration
  • Build hands-on experience with deploying airflow and submit airflow jobs using docker on Kubernetes
Cloud computing plays a more and more important role in current days. Applications and services are typically run on servers, which are comprised of CPU-processor, RAM-memory and storage-HDD, SSD. Instead of owning and provisioning servers in the on-prem data center, you could RENT the compute power and move it into the cloud. This means cloud computing is an on-demand delivery of computing power, database storage, applications and other IT resources through cloud services platforms via the internet. Cloud providers(Amazon Web Services-AWS, Google Cloud Platform(GCP), Microsoft Azure) provide rapid access to flexible and low-cost IT resources.
  • Learn the fundamentals of AWS and GCP
  • Learn how to work with different services provided by AWS and GCP
  • Hands-on experience with setting up an end-to-end pipeline across multiple services on AWS and GCP
SQL is one of the top skills of a data engineer. Whether it's relational database queries or working with NoSQL database queries, data engineers need to know how to extract, transform, and load data. In the database section of the program, we cover many advanced database concepts such as indexing, partitioning, sharding, and query optimization. SQL is becoming a universal language in the big data era, we will cover the differences among different database systems and computing frameworks such as RDBMS, Hive, Presto, Spark SQL, etc.
  • Understand different relational database systems such as MySQL and Postgres
  • Understand NoSQL databases such as Cassandra, Elasticsearch and DynamoDB
  • Understand the differences between SQL and NoSQL and their industry use cases
  • Gain hands-on experience with database indexing, sharding, and partitioning
  • Become proficient in SQL query optimization
What makes data engineering both exciting and challenging in recent years is the shift from the traditional data warehouse to the data lake and even the new data lakehouse approach. In the data warehouse part of the program, we will cover the fundamental concepts of data modelling, star schema and snowflake schema. Students will learn how to create ER diagrams and implement their own data warehouse. Modern tools and technologies such as BigQuery, Redshift, and Snowflake will be covered as hands-on labs so students get to experience how it works in practice. We will also cover different scenarios where each approach is a better fit for the problem.
    It's not just a career center. We support our students by understanding your career goal and interests.
    • You will complete several hands-on projects in this program
    • Start building your resume in the first week of your experience and keep improving it over time
    • Get your resume critiqued by industry experts and hiring managers who have built data engineering teams before
    • You learn how to build a killer portfolio website/GitHub that will impress hiring managers
    • Our hiring partners trust our students' abilities and hands-on real-world experience
    • Our alumni are resourceful, helpful, and supportive
    • Tap into our local recruiting network for senior level positions
    • Get coffee chat opportunities with WeCloudData's guest lecturers, mentors, and alumni
    • Our 13k+ data community gives you ample opportunities for networking
    Learn the basics of Spark and Hadoop.
    • Ability to process the large scale dataset using Spark and Hadoop
    • Hands-on experience with setting up Spark projects using both Scala and Pyspark
    Apache Airflow is an open-source workflow management platform to programmatically author, schedule, and monitor workflows. It is one of the most robust platforms used by Data Engineers for orchestrating workflows or pipelines. You can easily visualize your data pipelines' dependencies, progress, logs, code, trigger tasks, and success status.
    • Understand the basics of Apache Airflow
    • Hands-on experience with automating your data pipeline using Apache Airflow
    • Develop your ability to maintain and trouble-shoot an Airflow pipeline
    Data Ingestion is the first step of a big data processing system and it is essential for the Data ETL pipeline. The data ingestion layer is the backbone of any analytics architecture. Downstream reporting and analytics systems rely on consistent and accessible data. As a Data Engineer, Apache NiFi, Apache Kafka, AWS Kinesis are important and commonly used tools for Data Ingestion.
    • Learn different Data Ingestion tools
    • Ability to process data from different sources using the Data Ingestion tools
    • Hands-on experiences with connecting Data Ingestion tools with the downstream tasks
    What makes data engineering both exciting and challenging in recent years is the shift from the traditional data warehouse to the data lake and even the new data lakehouse approach. In the data warehouse part of the program, we will cover the fundamental concepts of data modelling, star schema, and snowflake schema. Students will learn how to create ER diagrams and implement their own data warehouse. Modern tools and technologies such as BigQuery, Redshift, and Snowflake will be covered as hands-on labs so students get to experience how it works in practice. We will also cover different scenarios where each approach is a better fit for the problem.
    • Learn the basics of NoSQL databases
    • Understand the key features of NoSQL databases
    • Learn how to work with NoSQL databases


    Watch our recorded webinar and learn more about data career and industry insights.
    Data Engineering Program Info Session
    Data Engineer Career Panel Discussion
    Meet Your Faculty: Zheng Xu
    Meet Your Faculty: David Tian

    Instructors & Guest Speakers

    past guest speakers
    Learn from the experts working in Data Engineering
    Jolay Zhang
    SDEIII/Architect (Amazon) | AWS Instructor (WeCloudData)
    Yongning Zhang
    Software Development Engineer @ Amazon
    Michelle Miao
    Data Engineer, Credit Sesame

    Portfolio Projects

    Gain hands-on experience with portfolio projects
    Data engineering is a very practical subject and you will need skills to solve diverse categories of problems to learn effectively. WeCloudData excellently incorporates hands-on training at every stage of the program. Students will have to complete two portfolios projects by the end of the program. They mirror real-world data engineering challenges which prepares students for post-bootcamp industry experience.
    Portfolio Projects
    • Use Spark, AWS cloud services and Apache Airflow to build a batch data architecture for BI dashboards.
    • Use Spark Streaming, Kafka, AWS cloud services and Lakehouse to build a data streaming platform.
    Online Learning Platform

    Learn anywhere, anytime

    Track your learning journey
    Watch lecture recordings, work on challenges, ask for TA help, and get resume and job support. The learning portal allows you to track your entire learning journey with ease.
    Sharpen your coding skills
    Leverage our online coding tool to test your knowledge, identify your weaknesses, and improve your Python and SQL coding skills. The LeetCode style live coding challenges will help you get prepared for technical job interviews.
    Get your career support
    Set job search objectives and track your journey. Receive resume support from your mentors and book one-on-one mock interviews. Get access to our internal job board and get referred to our hiring partners.​
    Career Services

    1-1 career mentoring by real data experts

    6-month mentorship after graduation
    Receive one-on-one (1-1) counseling to set your career goals, assist your job search, and track your progress.
    Build up your industry network through guest seminars, hiring panel discussions, and hiring partner demo workshops.
    Portfolio & resume revision
    Build a resume and professional data portfolio to demonstrate your skills and robust professional experience. Get professional profile pictures shot by a commercial photographer, and polish your online professional brand with blogs and LinkedIn.
    Interview preparation
    Prepare for your behavioural interviews through professional communication coaching. Set yourself apart in technical interviews by doing one-on-one mock interviews, take-home assignments, whiteboarding, and technical challenges.
    Meet our mentors
    Gleb Korolkov
    Data Engineer @ AWS
    Michelle Miao
    Data Engineer, Credit Sesame
    Ryan Kang
    Director, Machine Learning Product Engineering, RBC
    Carol Ye
    Data Scientist, Bell Canada
    student stories

    Success Stories

    Everyone at WeCloudData cares about your success and help is just one click away if you need assistance with understanding certain concepts. By taking this program you would learn a lot of highly demanding skills such as cloud platforms (AWS/GCP), big data tools Hadoop and Spark, DataOps tools Git, Docker, Kubernetes, and many others. The most important part of the full-time program is the ability to work on real business problems and gain valuable experience, which will help you to get your dream job.
    Stan Taov
    Data Engineering Bootcamp, 2021
    Schedule, Tuition & Financing Options

    Looking for special discount?

    Admission Process

    Step 1

    Book a
    Counseling Meeting

    Our program advisor will have a one-on-one meeting with you to see if the program is a good fit. There is no application fee. It takes about 30 minutes.
    Step 2

    Reserve the Spot &
    Sign the Contract

    Our admissions officer will work with you directly to help you fill out a contract, pay a $500 deposit and assist you in applying for any kind of grants and finance options.
    Step 3

    Start your
    Pre-bootcamp Learning

    Starting ahead will gain you more experience and competence. Research shows that preview and preparation account for 73.7% success in academic achievement of university students.

    Speak to our advisor

    Our Program Advisor can answer all your questions and help you pick a program that best suits your need. You can leave your information and we will contact you.

    You can also contact us at or (647) 588-4206

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    Frequently Asked Questions


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    Portfolio Course

    Data Engineer Client Project (Career Mentorship)

    Diploma Program

    Data Engineering Bootcamp (Full-Time)


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    Data Engineering Bootcamp (West Coast)

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