Data Engineering System Design

Data engineering system design interview resources. Posted by 6 months ago. Data engineering system design interview resources. I have an interview coming up in about a week. They told me it would be system design, and i think it will be heavily geared towards data/ml engineering since that's what the role is for. At its most fundamental, a database is responsible for the storage and retrieval of data for an application. A database can also be called a database management system (dbms) because it’s an application that manages access to a physical data store. The core functions of a database are to:

Data engineering system design interview resources. I have an interview coming up in about a week. They told me it would be system design, and i think it will be heavily geared towards data/ml engineering since that's what the role is for. At its most fundamental, a database is responsible for the storage and retrieval of data for an application. A database can also be called a database management system (dbms) because it’s an application that manages access to a physical data store. The core functions of a database are to: A data architect is responsible for all the design, creation, manage, deployment of data architecture and defines how data is to be stored and retrieved, other decisions are made by internal bodies. Few influences that can have an effect on data architecture are business policies, business requirements, technology used, economics, and data. Data design in software engineering. Data design is the first design activity, which results in less complex, modular and efficient program structure.

Posted by 6 months ago. Data engineering system design interview resources. I have an interview coming up in about a week. They told me it would be system design, and i think it will be heavily geared towards data/ml engineering since that's what the role is for. At its most fundamental, a database is responsible for the storage and retrieval of data for an application. A database can also be called a database management system (dbms) because it’s an application that manages access to a physical data store. The core functions of a database are to: A data architect is responsible for all the design, creation, manage, deployment of data architecture and defines how data is to be stored and retrieved, other decisions are made by internal bodies. Few influences that can have an effect on data architecture are business policies, business requirements, technology used, economics, and data.

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Spotify Data Engineer - System Design Interview



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Resources
- Spotify Data Engineer Interview Guide: prepfully.com/interview-guides/spotify-data-engineer

About video
Watch Udit from Prepfully deep-dive into the Spotify Data Engineer system design interview. By the end of this video, you’ll know what to expect, what the interviewers are looking for, and tips & tricks to ace the interview!

0:00 - 0:23 - Introduction
0:23 - 1:09 - Interview Core
1:09 - 1:50 - What is the interviewer looking for?
1:50 - 3:07 - Tips
3:07 - 4:06 - Outro

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Uber Data Engineer Interview: Design a Ride Sharing Schema



Today I'm interviewing Jitesh again on a data engineering and data modeling question around designing a schema for a ride sharing company like Uber or Lyft.

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Video Breakdown:
0:30 - Clarifying questions about the backend and functionality
2:28 - Initial design and solution for latency
11:18 - How would you design for analytics
19:15 - What does the schema look like all together?
22:34 - What's the benefit of a partition?

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Preparing For A Data Engineering Interview: How To Design A Data Warehouse For.A Food Delivery App



Data warehouses (in all their forms and iterations) have become the backbone of almost every organizations analytics, data science and BI departments.

Over the years they have evolved and taken on new shapes as modern infrastructure has been developed to better manage analytical queries and workloads.

In our last few articles and videos we discussed why data warehouses are used as well as a high level for what they are used for.

Now we wanted to provide more depth to a data warehouse.

Beyond just talking about the high level reasons why you might want to incorporate a data warehouse into your infrastructure. We wanted to discuss the key design components.

A common interview question for data engineers and BI developers is to develop a data warehouse. Personally, I have been asked to design a parking lot data warehouse, a college courses data warehouse and several others for interviews.

I suggest that most people watch a few videos on the topic of data modeling as well as read up on Kimball’s data warehouse design book. After that, then you should think about a few workflows you might enjoy and practice modeling them.

For example, let’s walk through designing a data warehouse for a food delivery app.
How would you approach this design?

Generally, a good way to start is to list out the entities you would consider being part of a food delivery app.

For example here is a list:
* Menu Items(And possibly add-ons)
* Restaurants
* Drop Off Locations 
* Cars
* Persons(Customers and drivers, since a driver in the future might be a customer and visa versa)
* Orders

This would be a good high level set of entities to start with. Especially in an interview. You don’t want to focus on every possible issue and detail. 

I would list these out and prod the interviewer to see if this is all the entities they were concerned with. Often times interviewers have a specific set of questions they want to ask. So if you don’t include all the entities, they may ask about different parts of the workflow you might have forgotten.
From here, the dimensions it may be obvious. You have menu items, restaurants, drop off locations, cars and persons.

These are all dimensional items because they represent entities that don’t change often, don’t contain measurable data and can be used to pivot and break down your future reports.

If you want to learn more, then watch the rest of the video! Or consider watching some of our other content.

What is a data warehouse and why build it?
theseattledataguy.com/what-is-a-data-warehouse-and-why-we-build-them-a-video/

Why invest in a data warehouse?
theseattledataguy.com/invest-data-warehouse/

Facebook System Design Interview: Design an Analytics Platform (Metrics & Logging)



Don't leave your system design interview to chance. Sign up for Exponent's system design interview course today: bit.ly/3K0lTtS

Watch our mock Facebook system design interview. Neamah asks Hozefa (Facebook, Wealthfront EM) a system design question on building a metrics and logging service.

Watch more videos here:
- Amazon SDE answers binary tree question: youtu.be/thkuu_FWFD8
- Google SWE answers algorithms interview question: youtu.be/NRRyk0XqkkA
- Google TPM answers Tiktok system design interview question: youtu.be/Z-0g_aJL5Fw
- Microsoft SWE answers algorithms interview question: youtu.be/oD1m1iREKB4

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ABOUT US:
Did you enjoy this interview question and answer? Want to land your dream career? Exponent is an online community, course, and coaching platform to help you ace your upcoming interview. Exponent has helped people land their dream careers at companies like Google, Microsoft, Amazon, and high-growth startups. Exponent is currently licensed by Stanford, Yale, UW, and others.

Our courses include interview lessons, questions, and complete answers with video walkthroughs. Get access to hours of real interview videos, where we analyze what went right or wrong, as well as our 1000+ community of expert coaches and industry professionals, to help you get your dream job and more!

#systemdesign #facebook #software #engineeringmanagement #tech #entrepreneurship #exponent #tpm

Chapters -
00:00:00 - Introduction
00:00:33 - Clarifying questions
00:01:52 - Requirements
00:07:34 - API
00:10:12 - Design
00:21:02 - Interview analysis

System design basics: Real-time data processing



#realtimedataprocessing #streamprocessing #dataprocessing
#systemdesigntips #systemdesign #computerscience #learnsystemdesign #interviewpreperation #amazoninterview #googleinterview #uberinterview #micrsoftinterview
In this video learn how to process messages or data in real-time.

What is Data Pipeline | How to design Data Pipeline - ETL vs Data pipeline



What is Data Pipeline | How to design Data Pipeline? - ETL vs Data pipeline
#datapipeline

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3) Crunching Data Series (2020) - youtube.com/playlist?list=PLcnJIHtHiTA2HmIleev4scARSFwrQ0bIy

Hi Friends, I am Anshul Tiwari, and welcome to our youtube channel I.T. k Funde.

More about this video -
In this video, we will understand what is a data pipeline with the help of a real-life example. Data pipelines are designed to move data from one point to another. In this video, we will cover below topics -

1 - What is a Data Pipeline?
2 - Why you need a data pipeline?
3 - Basic design of a data pipeline
4 - Types of Data Pipeline - Batch, Streaming, Lambda architecture
5 - Advanced data pipeline design

We will also learn about various products that can be used in a data pipeline - SAP BODS, Mongo DB, Apache Kafka, Big Query, MDM, Teradata, SAP Business Objects, Tableau.

Credits & Resources -
Wikipedia
alooma.com/blog/what-is-a-data-pipeline

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Delivering High Quality Analytics at Netflix



Netflix is a data-driven entertainment company, where analytics are extensively used to make informed decisions on every aspect of the business. As such, when something goes wrong — and, inevitably, it will — it’s imperative that it’s quickly caught, communicated, and fixed.

In this talk, Michelle Ufford will share how the Data Engineering & Analytics team at Netflix does exactly that. She'll describe their analytics environment and how data is used across a variety of roles, then delve into how Netflix is tackling common analytics challenges affecting data quality.

Database Design Tips | Choosing the Best Database in a System Design Interview



One of the most important things in a System Design interview is to choose the right Database for the right use case. Here is a cheat sheet that can help you choose the right DB for most of the use cases that you can encounter.

Summary of the video: codekarle.com/system-design/Database-system-design.html

Author: linkedin.com/in/sandeep1904/

We do over some important topics like which database you should use, in what scenarios, in a System Design Interview. Some comparisons between SQL and NoSQL databases, how to use multiple databases together in a real-world system, etc.

Chapters

0:00 - Intro
1:05 - Things that matter
1:45 - Caching
3:20 - File storage
4:22 - CDN
5:11 - Text search engine
6:30 - Fuzzy text search
8:25 - Timeseries databases
10:11 - Data warehouse / Big Data
11:17 - SQL vs NoSQL
11:24 - Relational DB
14:28 - NoSQL - Document DB
16:28 - NoSQL - Columnar DB
18:23 - If none of these are required
19:03 - Combination of DBs - Amazon case study.

#codekarle #databases #systemdesign #system #design #interview #amazon #faang

Amazon System Design Interview: Design Parking Garage



Don't leave your system design interview to chance. Make sure you're interview-ready with Exponent's system design interview prep course. tryexponent.com/courses/system-design-interview

Don't leave your system design interview to chance. Sign up for Exponent's system design interview course today: bit.ly/3NDsBIA

Watch our mock Amazon system design interview. Neamah asks Timothy, Amazon/Airbnb software engineer, a question on how to design a reservation and payment system for a parking garage.

Watch more videos here:
- Amazon SDE answers binary tree question: youtu.be/thkuu_FWFD8
- Google SWE answers algorithms interview question: youtu.be/NRRyk0XqkkA
- Google TPM answers Tiktok system design interview question: youtu.be/Z-0g_aJL5Fw
- Microsoft SWE answers algorithms interview question: youtu.be/oD1m1iREKB4

👉 Subscribe to our channel: bit.ly/exponentyt
🕊️ Follow us on Twitter: bit.ly/exptweet
💙 Like us on Facebook for special discounts: bit.ly/exponentfb
📷 Check us out on Instagram: bit.ly/exponentig

ABOUT US:
Did you enjoy this interview question and answer? Want to land your dream career? Exponent is an online community, course, and coaching platform to help you ace your upcoming interview. Exponent has helped people land their dream careers at companies like Google, Microsoft, Amazon, and high-growth startups. Exponent is currently licensed by Stanford, Yale, UW, and others.

Our courses include interview lessons, questions, and complete answers with video walkthroughs. Get access to hours of real interview videos, where we analyze what went right or wrong, as well as our 1000+ community of expert coaches and industry professionals, to help you get your dream job and more!

#systemdesign #amazon #airbnb #swe #tech #entrepreneurship #parking #exponent #tpm

Chapters -
00:00:00 Introduction
00:00:37 Question
00:00:53 Clarifying questions
00:02:55 Answer
00:03:11 APIs
00:09:34 Scale
00:10:55 Data types
00:19:56 Design
00:23:27 Trade-offs
00:26:15 Interview analysis
00:28:33 Tips

Data Engineering Patterns and Principles



dataplatformschool.com/

Interview: Amazon Data Engineer (Majoring in Computer Science to working as Data Engineer)



Data is the new currency for the future. Meet Rahul Narakula, who works as a Data Engineer at Amazon handling data to analyze what we know today and to forecast the future based on the insights. In this video, he shares what data engineering is, how he got into the role, his day-to-day, and his secret resources on cracking the data interview. Below are the questions I asked.
-
00:14 tell me about yourself
02:42 what is data engineering?
04:51 why data engineer not SDE after studying CS?
06:37 process of getting into Amazon
09:42 what do you do as a data engineer?
11:19 did you have any learning curves?
12:18 what do you like most/least about your role?
13:20 Amazon culture and work life balance
14:25 advice for those who want to join Amazon as a data engineer
-
Free resources for Data Engineering Interview Preparations:
Data Modelling: learndatamodeling.com/blog/category/data-modeling/
Product Sense: stellarpeers.com
Interview Structure Guide: prepfully.com/interview-guides
System Design: github.com/donnemartin/system-design-primer
System Design: educative.io (courses Groking the system design) (paid)
-
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My name is Yong and I am here to help you with your Career success. In this channel, I usually talk about Career Development (FAANG, interview tips, jobsearch hacks, networking tips and more), interview people working at awesome companies and about getting an MBA (and more). I now work at Amazon as a Sr. Product Marketing Manager in the retail business. I am originally from Seoul, South Korea and moved to the US to get my MBA at UNC Kenan-Flagler Business School. When I got that job offer from Amazon, I promised myself that I would help people for their career success and here I am.

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The opinions expressed in this video are those of the individuals. They do not purport
to reflect the opinions or views of any organization or its members.

Top 10+ Data Engineer Interview Questions and Answers



In today’s video, I will talk about the data engineering interview and go over the different types of questions that might get asked during the interview. Plus, we’re having a giveaway!

If you need more interview questions, we have compiled a list of the Top 100 Data Engineer Interview Questions for 2022:
interviewquery.com/p/data-engineer-interview-questions

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00:00 - Intro
00:24 - Behavioral Interview Questions
01:15 - The STAR method
02:01 - Basic Data Engineering Questions
02:49 - SQL Interview Questions
04:48 - Data Structures and Algorithms Questions
07:15 - Database Design and Data Modeling Questions
09:01 - Data Pipeline & ETL Questions
10:34 - Data Engineering Case Study
12:22 - Quick Tips

If you want to practice for your next interview, here is our Mock Interview Playlist: youtube.com/playlist?list=PLXXms4piUg2gZXEEQRxXzkbPxVqLKsxaT

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#DataEngineer #DataEngineerInterview #Giveaway #InterviewPreparation

Amazon Data Engineer Mock Interview + Tips and Feedback!!



Today I interview Scott who works as a machine learning engineer and data engineer at Nextdoor.

Want to be featured in the next mock interview video? Apply here: airtable.com/shrdQrwKK7xxGLm6l

👉 Subscribe to my data science channel: bit.ly/2xYkyUM
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🐦 Follow us on Twitter: twitter.com/interview_query

Scott has worked at big companies like Amazon and small startups with under 10 people. He's done it all from backend engineering to scaling data systems to now working as a machine learning engineer at Nextdoor.

We went over a sample question from Amazon at the end go over general feedback on how he feels about interviews and any tricks he uses. For the rest of the video you can find it on Interview Query.

More from Jay:
Follow me on Twitter: twitter.com/datasciencejay
Follow me on LinkedIn: linkedin.com/in/jay-feng-ab66b049/

Related Links:
Amazon Machine Learning Interview Questions: interviewquery.com/blog-amazon-machine-learning-interview-questions-solutions/
Amazon Data Engineer Profile: interviewquery.com/interview-experiences/amazon/data-engineer#
Amazon Business Intelligence Interview: interviewquery.com/blog-the-amazon-business-intelligence-engineer-interview/
Data Engineer SQL Questions: interviewquery.com/p/data-engineer-sql-questions
How to Prepare for a Data Engineering Interview: interviewquery.com/p/how-to-prepare-data-engineer-interview

Stanford MLSys Seminar Episode 5: Chip Huyen



Episode 5 of the Stanford MLSys Seminar Series!

Principles of Good Machine Learning Systems Design
Speaker: Chip Huyen

Abstract:
This talk covers what it means to operationalize ML models. It starts by analyzing the difference between ML in research vs. in production, ML systems vs. traditional software, as well as myths about ML production.

It then goes over the principles of good ML systems design and introduces an iterative framework for ML systems design, from scoping the project, data management, model development, deployment, maintenance, to business analysis. It covers the differences between DataOps, ML Engineering, MLOps, and data science, and where each fits into the framework. It also discusses the main skills each stage requires, which can help companies in structuring their teams.

The talk ends with a survey of the ML production ecosystem, the economics of open source, and open-core businesses.

Speaker bio:
Chip Huyen is an engineer who develops tools and best practices for machine learning production. She’s currently with Snorkel AI and she’ll be teaching Machine Learning Systems Design at Stanford from January 2021. Previously, she was with Netflix, NVIDIA, Primer. She’s also the author of four bestselling Vietnamese books.

--

Check out our website for the schedule: mlsys.stanford.edu
Join our mailing list to get weekly updates: groups.google.com/forum/#!forum/stanford-mlsys-seminars/join

#machinelearning #ai #artificialintelligence #systems #mlsys #computerscience #stanford #stanforduniversity #snorkel #snorkelai #netflixai #nvidia

How Data Engineering Works



So, the sole purpose of data engineering is to take data from the source and save it to make it available for analysis. Sounds simple, but it’s the matter of the system that works under the hood.

Watch our video to find out more about data engineering:
00:00 Basic Data Infrastructure
02:07 ETL Pipeline
04:34 Data Warehouse
06:07 Data scientists and data engineers
08:05 Big Data
09:45 Data streaming
11:47 Distributed Computing

Sources:
[1] sre.google/sre-book/eliminating-toil/
[2] statista.com/statistics/419778/paypal-annual-payments/
[3] forbes.com/sites/bernardmarr/2019/08/23/the-amazing-ways-youtube-uses-artificial-intelligence-and-machine-learning/?sh=3752a1d75852

To learn more check our articles:
1) What is Data Engineer: Role Description, Responsibilities, Skills, and Background altexsoft.com/blog/what-is-data-engineer-role-skills/?utm_source=youtube&utm_medium=link&utm_campaign=howdataengineeringworks
2) Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role altexsoft.com/blog/datascience/what-is-data-engineering-explaining-data-pipeline-data-warehouse-and-data-engineer-role/
3) Big Data Engineer: altexsoft.com/blog/big-data-engineer/
4) What is ETL Developer altexsoft.com/blog/datascience/who-is-etl-developer-role-description-process-breakdown-responsibilities-and-skills/

Learn more about AltexSoft: altexsoft.com/
Follow us on LinkedIn: linkedin.com/company/altexsoft/
Follow us on Facebook: facebook.com/altexsoft/
Follow us on Twitter: twitter.com/AltexSoft
Follow us on Instagram: instagram.com/altexsoftcom/

Music in video by Kevin MacLeod ( incompetech.filmmusic.io): Sneaky Snitch, Sheep May Safely Graze - BWV 208, Wholesome, Disco Sting, Krampuss Workshop, Thinking Music, Whiskey on the Mississippi, Hidden Agenda, Egmont Overture, Sheep May Safely Graze, Holiday Weasel, Brittle Rille, March of the spoons, Hidden Agenda, Fuzzball Parade, Gothamlicious, Light Sting.
License incompetech.filmmusic.io/standard-license

Want to Get Better at the System Design Interview Start Here!



System Design interviews are HARD. This video will give you a great start at mastering the art of system design. I will provide you some insight into the system design interviews, recommend some great books, some free resources and give you interview advice -- what to do, and what not to do!

👩🏼‍💻 Get a BIG DISCOUNT on LeetCode Premium Annual Subscription
leetcode.com/subscribe/?ref=I0zWcC0x

SYSTEM DESIGN ONLINE RESOURCE

Grokking the System Design Interview & Grokking the Advanced System Design Interview courses @ Educative
To get 10% off, follow the link: educative.io/engineeringwithutsav

SYSTEM DESIGN BOOKS

Web Scalability for Startup Engineers - amzn.to/39c55QV
Designing Data Intensive Applications - amzn.to/3fxgOLm
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Domain Driven Design - amzn.to/2UUPXza

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LOW LEVEL DESIGN BOOKS

Clean Architecture - amzn.to/3kZ7UqR
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Site Reliability at Google - sre.google/books/
Distributed Systems for Fun and Profit - book.mixu.net/distsys/

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TIMESTAMPS

00:00 Introduction
01:48 Interview Types
02:44 Books for System Design
07:40 Bonus Books
09:45 Books for Product Design
13:34 Domain Specific Books
15:07 Interview Tips and Preparation Advice

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Creating a Data Engineering Culture | Big Data Institute



Get the slides: datacouncil.ai/talks/creating-a-data-engineering-culture

Download slides of this talk: dataengconf.com/speaker/creating-a-data-engineering-culture?utm_source=youtube&utm_medium=social&utm_campaign=%20-%20DEC-BCN-18%20Slides%20Download

ABOUT THE TALK:

The biggest initial hurdle to success with Big Data isn’t technical - it’s management. Your data engineering project’s initial success is predicated on your management team correctly staffing and resourcing it. This runs opposite to how most data engineering teams are started and run. If you just choose the best technologies, things will just fall into place. They don’t and that’s a common pattern for failure.

But how do you correctly do something that’s so new? This could be your team’s first data engineering project. What should the team look like? What skills should the team have? What should you look for in Data Engineer (because you’ll probably have to hire a Software Engineer and train them)? What are some of the management pitfalls?

In this talk, we will cover the most common reasons why data engineering teams fail and how to correct them. This will include ways to get your management to understand that data engineering is really complex and time consuming. It is not data warehousing with new names. Management needs to understand that you can’t compare a data engineering team to the web development team, for example.

Jesse will share the stories of teams who haven’t set up their data engineering culture correctly and what happened. Then, Jesse will talk about the teams who’ve turned around their culture and how they did it. FInally, Jesse will share the skills that every data engineering team needs.

ABOUT THE SPEAKER:

Jesse Anderson is a Data Engineer, Creative Engineer and Managing Director of Big Data Institute.

He trains at companies ranging from startups to Fortune 100 companies on Big Data. This includes training on cutting edge technology like Apache Kafka, Apache Hadoop and Apache Spark. He has taught thousands of students the skills to become Data Engineers.

He is widely regarded as an expert in the field and his novel teaching practices. Jesse is published on O’Reilly and Pragmatic Programmers. He has been covered in prestigious publications such as The Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired.

ABOUT DATA COUNCIL:
Data Council ( datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers. Make sure to subscribe to our channel for more videos, including DC_THURS, our series of live online interviews with leading data professionals from top open source projects and startups.

FOLLOW DATA COUNCIL:
Twitter: twitter.com/DataCouncilAI
LinkedIn: linkedin.com/company/datacouncil-ai
Facebook: facebook.com/datacouncilai
Eventbrite: eventbrite.com/o/data-council-30357384520

5 Tips for System Design Interviews



Here are 5 Tips for System Design interviews. They are helpful when preparing for a System Design interview.

1. Don't get into details prematurely

2. Avoid fitting requirements to a set architecture in mind

3. Keep it simple, stupid! Remember to look at the big picture and avoid too many hacks when solving.

4. Have justifications for the points you make. Don't use buzz words or half hearted thoughts in your design.

5. Be aware of the current solutions and tech practices. A lot of solutions can be purchased off the shelf which simplify implementation. You should be able to argue for a custom implementation with it's pros and cons.

Have these on the back of your mind during you interview, and all the best!
Here are three major points evaluated during the interview:
1. Clarity of Thought

a. Express your thoughts in a clear manner.

b. Justify your decisions. Critical reasoning and argument are key to a successful software design.

c. When faced with a problem, use standard approaches to mitigate it. For example, say you are faced with an availability problem. State that replication and partitioning help increase availability in general, and move on to offer a solution.

d. Don’t make points without thinking them through. Half-hearted attempts at solving problems are frowned upon heavily.

2. Know about existing solutions

a. Stay up to date with the current solutions in the market. This includes products and design practices. If NoSQL is being adopted left right and center, you need to be aware of it.

b. Know when to pick a solution vs. building something custom. If you name a product, you should be (generally) aware of the features it provides.

c. Design practices enable you to meet custom requirements. Examples are decoupling systems, load balancing, sticky sessions, etc…

3. Flexibility

a. Switch your targets as the requirements shift. If the interviewer wants to know about one particular part of the system, do it first.

b. Never have a set architecture in mind. We all try to fit requirements to a system, but only after it has been shaped by the initial ones. A rigid attitude creates a brittle architecture. It will break before you do.

c. Take a step back at times to make adjustments to the general architecture. Being focused on one part can narrow our vision and bloat those areas. There will be components which can be extracted out and extended to the rest of the system.

Looking to ace your next interview? Try this System Design video course! 🔥
get.interviewready.io?source_id=tipsforsd

With video lectures, architecture diagrams, capacity planning, API contracts and evaluation tests. It's a complete package.
Use the coupon code 'earlybird' for a 20% discount!

5 Data Engineering Projects Ideas To Put On Your Resume



Dice's 2020 tech jobs report cites Data Engineering as the fastest growing job in 2020. Increasing by a staggering 50%, while Data Science roles only increased by 10%.

You can rest assured that the influx of data engineering will not regress anytime soon. To bolster this supposition, the International Data Group (IDG) predicts that the five year compound growth rate (CAGR) of data utilization from 2021 to 2024 will outweigh the total data creation spanning the entirety of the last thirty years. Yes, you heard that correctly, thirty years, dating back far before the origins of both FaceBook, YouTube and Amazon.

We have established that data engineering is a well-paying position, in one of the fastest-growing tech fields, with relatively low competition. What is not to love?

So let's add a few data engineering project ideas to your resume.

If you want to learn more about data engineering, check out Googles Data Engineering Course
bit.ly/3c3woxu

If you'd like to read up on my updates about the data field, then you can sign up for our newsletter here.

seattledataguy.substack.com/​​

What Skills Do Data Engineers Need?
youtube.com/watch?v=LgSHaOvNodA

If you like this video, then subscribe to the channel!
youtube.com/channel/UCmLGJ3VYBcfRaWbP6JLJcpA?sub_confirmation=1

Projects Included In Video

HashtagCashtag
github.com/shafiab/HashtagCashtag

Scraping Rental Prices
sspaeti.com/blog/data-engineering-project-in-twenty-minutes/

Github Data Analytics
hoffa.medium.com/400-000-github-repositories-1-billion-files-14-terabytes-of-code-spaces-or-tabs-7cfe0b5dd7fd#.qm2s97y25

Crawling For Inflation
github.com/uhussain/WebCrawlerForOnlineInflation
All signs point towards an auspicious future for data engineering.

Thanks to Clint for putting together this list of project:
linkedin.com/in/clint-morris-572604167/

However, merely graduating from a relative field alone will not qualify you for a data engineering position.

You'll need related real-world experience to fine-tune your hard skills. Concerning your future job search, one of the best ways to develop and convey these skills is through akin data engineering portfolio projects.

In this video, we will review five potential project ideas with data sources. Before we cover the projects, you need to know the skills you should include in potential projects. For that, we will explore the most in-demand skillsets for data engineers.

Check out my Medium here:
medium.com/@SeattleDataGuy​

If you need data consulting help, then reach out to our team here:
theseattledataguy.com/

0:00 Intro
4:37 Project #1 Hashtag Cashtag Project
7:45 Project #2 Scraping Rental Prices Into Druid
9:45 Project #3 Github Analytics
11:30 Project #4 Crawling For Inflation
12:59 Project #5 Scraping PredictIt

So what is your current data engineering project ideas?

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Data Engineering System Design, Spotify Data Engineer - System Design Interview, 5.63 MB, 04:06, 3,047, Prepfully, 2022-02-26T16:13:52.000000Z, 19, A block diagram of the data acquisition station's hardware components, www.researchgate.net, 850 x 862, png, System design is the process of designing the elements of a system such as the architecture, modules and components, the different interfaces of those components and the data that goes through that… Almost every it giant whether it be facebook, amazon, google, or any other ask various questions based on system design concepts such. In its core, data engineering entails designing the architecture of a data platform. Development of data related instruments/instances. , 20, data-engineering-system-design, Design Ideas

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