Data Engineering Bootcamp: Learn online, on your own time.

Switch careers to an in-demand tech role without quitting your job.

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Switch careers to one of the fastest growing jobs in tech

Companies of all sizes are now competing to hire data engineers who can manage their ever-growing infrastructure needs and help deliver value to the business.

Data engineering saw 50% growth in open roles in 2020

In the U.S., we see an average salary of $113,259 with 9.3% growth over previous year.

Companies like Amazon, Accenture and Capital One are all trying to hire for this role at a large scale, and, as a result, the average time to fill for data engineers is 46 days.

Learn with an industry expert in your corner
Mentor-guided learning not only helps you build skills faster, but also enables career growth.

Weekly 1:1 video calls

Get feedback on projects, discuss blockers, and refine your career strategy


Your mentor will help you stay on track so you can achieve your learning goals

Unlimited mentor calls

Get additional 1:1 help from other mentors in our community, at no extra cost.
"A perfect match for me, my mentor was friendly with a great eye for detail and broad industry knowledge. Legendary."
Jonathan Gerber
Data Science graduate, 2020
Marvin Edmond
Sr. Data Engineer
Ilia Semenov
Data Engineering Lead
Karthik Ramesh
Sr. Data Engineer
Sameera Poduri
Data Science Manager

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Fit learning into your life, with a team that has your back
In this 100% online program, you study on your own terms with the help of an expert mentor, student advisor, and career coach—all of whom are invested in your success.
Learn on your own time
No need to quit your job. View lessons and work on projects on your schedule.
Get unlimited 1:1 mentor support
Meet weekly with your personal mentor, with as many additional calls as you need.
Build study plans that work for you
Complete the course sooner by putting in more hours per week.
Learn cutting edge skills to make your portfolio stand out
Get job-ready with an industry-driven curriculum

The bootcamp covers 400+ hrs of course work, with a combination of lectures, readings, projects, and career resources that are geared towards technologies used by the most data-forward companies.

Big Data Engineering
Data Engineering in the Cloud
Data Pipelines and Orchestration
Data Virtualization and Container-based
Streaming Data and APIs
Interacting with Data
Coding for Data Engineering

In this module, you will learn Hadoop and Apache Spark. Employers including Amazon, eBay, NASA JPL, and Yahoo use Spark to quickly extract meaning from massive data sets across fault-tolerant Hadoop clusters.

  • Learn how to use batch processing and real-time processing
  • Translate complex analysis problems into iterative or multi-stage Spark scripts
  • Use Spark programming to explore and transform massive datasets at scale by writing high-performing programs

This module introduces you to the fundamentals of cloud computing and then teaches you to design data-intensive applications using various cloud components

  • Understand the core concepts of cloud computing (Compute, Networking, Security, Data security in-transit and at-rest)
  • Design highly-available and scalable cloud solutions for data engineering using Azure

In this module, you will learn an open-source platform to programmatically author, schedule, and monitor workflows in Apache Airflow. You will learn to design high-performing data pipelines and make sure they run well by monitoring the underlying resources

  • Design robust data pipelines using Apache Airflow
  • Monitoring the health of your data and pipeline using various tools and techniques including open-source monitoring tools, custom dashboards, and Cloud pipeline monitoring

You will learn how to use Docker, a widely-used platform that developers and administrators use to build, ship, and run distributed applications. You will also learn about Kubernetes, a production-grade system for managing complex applications using containers

  • Convert your applications and data processing pipelines to container-based application
  • Develop your own Docker images using Dockerfiles and practice Docker Compose
  • Orchestrate containers to deliver scalable and reliable performance using Kubernetes

In this module, you will learn how to use Apache Kafka, which is used in production by over 33% of the Fortune 500 companies such as Netflix, Airbnb, Uber, Walmart and LinkedIn.

  • Design pipelines to process Real-time Streams using Apache Kafka and Kafka Streams API
  • Design and test APIs for robust performance and security
  • Learn some API best practices using real-world examples (e.g. graceful degradation, HTTP verbs, Request validation, Logging, exception handling, etc.)

This section helps you build a strong foundation in data skills like data warehousing and data modeling which are important in order to decide the best way to store and retrieve data

  • Learn to explore large collection of business-related historical data that would be used to make business decisions
  • Build and organize complex queries to make them more readable with the WITH clause, and how to use set operations such as UNION, UNION ALL, EXCEPT, and INTERSECT to combine tables

You’ll learn how to write efficient Python code, a critical skill for any data analyst, data scientist, or data engineer. You will learn concepts such as functional programming, closures, decorators, and more

  • Practice python skills on projects covering data wrangling, web scraping, data parsing, and streaming data from sources like Twitter
  • Understand the performance difference between data structures such as hash tables, stacks, queues, and more
  • Use popular algorithms (like Greedy techniques, Divide and Conquer, Dynamic programming, Network flow) to improve application performance
  • Master essential GIT skills to develop collaboratively in teams

Request a detailed syllabus

Develop a strong portfolio to attract employers
In addition to small projects designed to reinforce specific technical concepts, you’ll complete two capstone projects focused on real-world data engineering problems that you can showcase in job interviews.
While working on the projects, you'll:
Collect and transform data using Spark and Hadoop and other cloud technologies
Optimize your code to improve query performance
Create a pipeline to automate these steps
Create a dashboard for monitoring the pipeline's performance and health
Kelly Sims
Graduated 06/2018
Capstone project: Cryptocurrency Price Prediction
David Albrecht
Data Science graduate
Capstone project: Capital Bikeshare Rebalancing
Changing careers is hard, but we’re committed to getting you there

Career-focused resources are paired with 1-on-1 coaching calls to help you land your dream job. You’ll have 7 scheduled calls, with access to more. Full career support continues for six months after completing the program.

Your career coaching calls will help you:
Create a successful job search strategy
Build your professional network
Find the right job titles and companies
Craft an eye-catching resume and LinkedIn profile
Ace the job interview
Negotiate your salary
""Springboard helped with career prep and the job search where we were exploring different companies I'd be interested in. We also did mock interviews and technical interviews.They put me in contact with a few different employers.""
Justin Knight
Data Science Career Track graduate 2018

Your success is ours - the numbers show it

Total students
who have enrolled in our Data Science Career Track since its launch in 2016
Job guarantee refund rate
among 328 eligible students who have completed the 6-month job search period
Average salary increase
from students who provided pre- and post-course salaries, through July 21, 2020

Is this program right for you?

This data engineering bootcamp was designed for students with some experience in a data analyst, data science, or software engineering role.

Prerequisites (any of the following are sufficient):

6+ months of work experience in any analytical role, ideally working with SQL
6+ months of work experience as a software engineer using Python or Java or C++
Bachelor's degree in CS or other degree that involves extensive programming skills
Not a good fit?

Consider our Data Analytics Career Track instead.

Learn more

More questions about the program?

Schedule a call with our Admissions team or email Orlando, our Admissions Manager, who will help you think through the decision.

The admissions process

Submit your application
Fill out our application form to get started. There is no application fee. It takes about 10-15 minutes. You should expect a reply in 1-2 business days.
Interview with an Admissions Director
We'll discuss your background and learning goals to make sure you're a good fit for the program.
Take the technical skills survey
If it's a fit, we'll send you a skills survey to test your data analysis and programming knowledge. Applicants spend up to 1.5 hours on this.
Join the program
If you pass the technical skills survey, we will send you a registration link. Choose the start date and payment plan that works for you (we can help!). You’ll be one of the fewer than 20% of applicants who secured a spot in the Data Engineering Career Track!
Fill out our application form to get started. There is no application fee. It takes about 10-15 minutes. You should expect a reply in 1-2 business days.

Course start dates

The Data Engineering Career Track is a 6-month program. Most students devote 15-20 hours a week to complete the course. You can complete the course earlier by putting in more time per week.


The full tuition of the program is $8,940. If you pay upfront, you get a 16% discount. Remember, if you don’t get a job within 6 months of completion, you’ll receive a full refund. See job guarantee eligibility terms

Scholarship eligibility: Are you a woman or a veteran?
Upfront discount
Pay upfront and save 16% on tuition
Paid at the time of enrollment $7,500
Total cost$7,500
Month to month
Pay only for the months you need, up to 6 months
Total: Up to $8,940
Paid at the time of enrollment$1,490
Monthly payments during course$1,490
Total costVariable (up to $8,940)
Climb Credit loan
Finance your education with low monthly payments
$52-104 */mo
Total: $10,160 - $11,523*
Paid at the time of enrollment$500
Monthly payments during course $52 - $104* (interest payments only)
Monthly payments after course$274-$303* for 36 months
Total cost $10,160 - $11,523* (Loan amount of $8,440)
*range varies based on approved interest rate and only available for U.S. residents
See how Springboard compares

Springboard is the best value bootcamp that gets you from beginner to job-ready for data engineering roles, while learning on your own time.

Springboard6 months
Insight2 months
Udacity5 months
Coursera4 months
Curriculum length (approx.)
Springboard400 hrs
Insight300 hrs
Udacity150 hrs
Coursera70 hrs
1-on-1 industry mentors
1-on-1 career coaching
Job guarantee
Coursera No
No. of capstone projects
Online, asynchronous

Apply for the Data Engineering Bootcamp

Secure your spot now. Seats are limited, and we accept qualified applicants on a first come, first served basis.


The application is free and takes 5-10 minutes to complete.

What is included in the course tuition?

400+ hour expert-curated curriculum
Weekly video calls with your mentor
Unlimited additional 1:1 mentor support
Active online student community
Support from community managers
Unlimited career coach calls
Resume and portfolio reviews
1-on-1 mock interviews
Access to our employer network
100% money-back guarantee
Frequently Asked Questions
Are there any prerequisites for this course?

You should have a strong analyst or software engineering background, and should be proficient in SQL and Python. If you do not meet these requirements, you may want to consider our Data Analytics Career Track instead.

How do the tuition payments work?

There are three payment options (all of which come with our job guarantee as long as you meet eligibility requirements):

  • Monthly plan: You pay $1,490 per month while you are enrolled in the program. If you take 6 months to graduate, your total payment is $8,940. If you graduate sooner, you pay less!
  • Upfront payment: You pay $7,500 upfront for 6 months. This is a 16% discount on the monthly plan.
  • Climb Credit loan: Available by application to qualifying U.S. citizens and permanent residents. If you are not a U.S. citizen or permanent resident, you can still apply for financing with a fully qualifying co-borrower who is a citizen or permanent resident, as long as you both have a U.S. address.
    • If approved, you pay $500 deposit to confirm your seat. You can finance the remaining $8,440 through a loan. You’ll make small interest-only payments for the first six months. After that, you will pay 36 monthly payments of $274-303 each. Learn more here
    • Please note: lending might not be available in all 50 states - click here for the current full lending list.

All charges will be in USD (based on the above prices). If you reside outside the U.S., this might carry an additional transaction fee, depending on the bank you use. We display prices in your local currency to give you an estimate of how much you will pay based on prevailing exchange rates, excluding transaction fees.

How does the admissions process work?

Spots are limited and we accept candidates on a rolling basis. We have a multi-step application process. The first step involves a 10-15 minute questionnaire to learn about your prior educational and work experience. Based on your responses, we might ask for additional information - e.g. a brief phone interview, or a quick data and coding skills survey - just to make sure the Data Engineering Career Track is a good fit for you.

What are the eligibility criteria and terms for the job guarantee?

A career transition into data engineering is exciting, but involves focused and consistent effort. We are thrilled to have your back in this journey and ask for an equal commitment from you. In order to be eligible for this job guarantee, you should:

  • be 18 years or older
  • hold a Bachelor’s degree from any educational institution in any subject, which is still a requirement by most employers for these roles
  • be proficient in spoken and written English, as determined by initial interactions with our Admissions team
  • be eligible to legally work in the United States, or in Canada if applying for positions in Toronto, for at least two years following graduation from the Career Track. See the detailed policy for further requirements about specific Visa types
  • you must have one of the following:
    • at least six months of professional experience (including internships and contracts) working in software engineering and development using a general purpose Object-oriented programming language, such as Python, Java and C++; OR
    • at least six months of professional experience working as a data analyst, data scientist, database administrator, ETL developer or any other analyst roles; OR
    • a Bachelor's degree or higher in computer science, math, electrical engineering, physics, data science, information science, financial engineering, applied stats or other degree that involves extensive programming experience
  • be able to pass any background checks associated with jobs that you apply for
  • apply to positions, dedicate sufficient time and effort, and follow the job search process recommended to you by our career coaches

Read the full eligibility criteria and terms here.