The Harsh Reality of Being a Data Engineer
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- Опубліковано 1 чер 2024
- Data Engineering is a great, fast growing field to pursue and build your career on but there are some major cons to keep in mind. In this video I talk about 3 things that Data Engineers face which makes the job really challenging.
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• Data Engineer Answers ...
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0:00 Intro and Overview
2:20 2nd Class Citizens
4:56 ProjectPro - Build projects
5:55 Dependencies
9:01 Outdated Tools and Tech
Check out ProjectPro for DE, DS, ML projects. This link gives you additional discounts: bit.ly/3GmbSq9
Thank you for watching. What are you thoughts on these topics? Let's talk! 😀
Thank you for this helpful video .. My question is that , Are Software Engineers and Data Engineers doing the same work..? because I have not much interested in software development and programming as usual ..SO, Will it be right choice for me to adopt this career as a Data engineer..? Please guide me .. I really appreciate your helpful videos and a lot of Respect from "PAKISTAN".
Do not forget that if a new director is coming you might get demoted/fired
@@fakhrabashir6471 no software engineering is different. They are more inclined towards web or app development while data engineers develop data pipelines that's generally not exposed to outside users
@@JashRadia Thank you so much.. your guidance always give me a right direction towards my career. May God bless you with healthy, wealthy life..❤️
The problem with the Business Analyst specialism is [as an intern/junior], employers expect you to have an MBA and/or prior business experience, a solid interest in business/finance in addition to the technical skills, which creates a significant barrier to entry. As a learner looking to change careers at a mature age, data engineering is far more attractive to me, because the emphasis is primarily on the technical skills.
Yes. Totally agreed!
@Ray wow, sounds like a very tough market in India if you don't have the right background. I think the situation is different in USA, although I'm in a European country. Hopefully your Masters will pay off eventually. Best wishes!
Isn't the main difference that implementation is different to theoretical understanding? A BA just has to understand the business and tech side, whereas the data eng or data analyst who is in the business have to know their side and be able to build/analyse things.
I agree it's a lot to learn though.
@@StellaratorAI A salary rarely pays what you are worth. Its a sad reality
@Ray I know direct conversion from USD to INR is useless way when making pay comparisons (or standard of living) but are you sure 4000$ in India > 150K$ in USA ? That seems very off
As a data engineer, I agree with your points but many of them are barely even negatives, at least for someone who would actually enjoy this kind of job. I enjoy being on the back end and a "second class citizen" as nobody is expecting me to pump out software like they do for the software engineers. The dependencies can get annoying but honestly the investigational work of this job is some of the most fun and keeps you engaged. Learning new software all the time is fun and it's cool to find better ways to do what you were doing before. Overall this job is a privilege to be able to work in as it has amazing WLB, fantastic pay, and low stress compared to 95% of other jobs in the world. Yes it has its challenges but it is nothing compared to other careers, the only hard part really is the initial learning curve.
I'm really interested to become data engineer in future but I really dk which btech degree I choose to pursue first bcuz I'm not that good at studies so Cse degree will be hard but I can get IT or data science
Very well put. For those who really like DE, this video will only help them like it more I guess 😅
Your opening skit got me. My team is basically data engineering, but also core development in our small company too. And once was in a project planning meeting that had some managers, project owners, and marketing/sales in it. The main project was just parsing out text from some documents to check for some sort of risk assessment compliance. And near the end after I just briefly explained my thoughts what doing this would entail for our team which was JUST importing data, parsing for certain identifiers, and generating reports; one of the marketing/sales guys asks, "So when we have this can we advertise this as AI and machind learning because that's big right now".
And I basically facepalmed(good thing it was a zoom meeting with my camera off) and got flustered and started say explaining why this wasn't AI and it would be a whole other thing to use that for this project. Which was apparently the wrong thing to say because he just asked why can't we do that? And I'm thinking, "nobody on our team has any experience with that so how can we build that product in your timeframe?" Luckily my boss jumped in and saved me to explain that we couldn't do that now and that it would be a huge time commitment and would derail the whole thing.
Yep it sucks how execs run behind the ML and AI keyword and try to fit it in whenever possible even if it doesn't make sense. Looks like it was a close call 😅
Thank you Jash for this frank video, this puts alot in perspective. I am currently transitioning from Warehouse executive to Data sphere and training to improve soft skills in visualization tool (Power Bi) and query language (MySQL). I end goal was and still is to be a Data Engineer, before now I had no idea these three things you mentioned 1. Second tier folks in most compnay 2. Dependency (bridge between producers and stake holders) and 3. Be Update with technology. This is most appreciated. Thanks also for the link to Project Pro cause I know for a fact, a ceritficate will not get me a job its practice and documentation of work done.
My sister is data engineer and I am very proud of her. She works 10 Hours a day. Some times i feels sad for her for her long working hours and it is taking serious toll on her health.
Excellent video, important points well-presented with real-world examples!
The ‘Dependencies’ section (6:00) illustrates why data (or software or most any other type of) engineering will not be eliminated by ChatGPT. AI will get better and better at dealing with the “this ain’t right” complaints, but it will be a while.
Yeah us Data Engineers are like doctors who people think, know the answer to all questions. I get question as well like "Why cant you do this? Why are we paying you all this money?" and my answer is usually "This is the job of an architect or a data scientist or ML engineer" and this infuriates them to the core.
Ikr! People usually don't notice things done in the backend 🤷♂️
I'm looking to move out of data engineering and closer to business decision making. All data roles are slowly becoming one. Data analyst, analytics engineer, data architect, cloud engineer, data engineer, data scientist. ALL of them. Regardless of what the job description says, the company will want you to be able to do everything. I can't take it anymore.
@@EH-it8pj yes it's too hard. Better to become a business analyst and just work with spreadsheets and let someone else deal with all the coding.
@@JashRadia we face the same thing, people value what analytics doing but not how they are able to do it.
@E H Yes, I'm looking to move OUT of data engineering. I've been a BI Developer, DBA, ETL Developer over the past 20+ years and currently working in the last few years as a data engineer. Over my career, data engineering is really the most unsatisfying role I have had in that is is basically moving data around with little regard to the final business question at hand. I'd rather USE the data to explain business solutions. Data engineering pays more, but is extremely boring.
Brilliant, making these types of videos help with communication skills, stuff that I have been told I lack of.
One thing that you have mentioned is the very broad tech skills we have to deal with, but you haven't said that sometimes it requires to switch from one to another with a snap of a finger. Some pipelines are failing and have to fix them, and at the same time doing your normal development work.
Good stuff, I suppose your work is key and haven't been affected by Google laid offs.
I am yet to know my fate but keeping positive! 😊
I'm a business analyst at a small company so some of the data engineering needs will be falling on my shoulders. This was a very informative video with great perspective!
Great to know, thanks!
Thanks Jash for bringing up much much valid situations and scenarios for data engineering.. 👍
Awesome !! love you bro.... your content is really helpful.
Coming from a datawarehouse background and I hear and see DE and DS I remember the need of data architecture and the use of a ETL tool for datawarehousing and BI. DS and DE give me the impression of anything goes and quick and dirty and after a while these projects tend to go to more structured, scd and maybe a need to use an ETL tool to realise that. So I miss a bit the added value of DE and DS over old school datawarehousing.
This video is so on point! data engineering is such fast-paced field that by the time you learn something, something else gains momentum and everyone starts following the trend. It is a never-ending process of learning and upgrading.
Thank you and yeah, well put.
Ohhh so that's why Data engineers move to Data Manager or Data Scientist role after a few year....
I always kept wondering why such good talents choose a different track ...
Changing technologies is the most important factor here...
unless someone is very passionate about learning new things Data engineering is going to be trouble for them
lol I have been working as a data engineer and I didn't even know. I created and maintain our current ETL pipeline. It is pretty simple but as I get data from various sources it gets complex. I can relate with the issues that can arise in such cases
Cool on the point view! Love it :)
Thanks for the video Jash.. you literally spoke my mind about DE being just the support function in Product Based and captive Industry. There is always a cap on budget and most of the stuff we do as a DE goes under the rug as the work wont get enough visibility to stakeholders.
Introductory part was pretty awesome. Good improvements in content presentation. Keep it up so we will also keep supporting you to grow.
Thank you so much!
Great video, really appreciated the insights on the challenges of being a data engineer
Thank you! 😊
loved the video and explanation
3:35 the Witcher shirt already had my attention but you really had my attention when you said you were a former Zser. I’m a current Zser who’s frantically watching these videos to understand the scope of growth of my role. Literally have a connect with my PD coach this week 😂
Thank you! And all the best 😊
After that opening skit, I love this guy!
Isn't that true for the DevOps/SRE roles too? Being a DevOps Engineer myself, I always feel like a "Second class citizen" in the sense that my work has little to do with the aspects of the application that are driving the whole business and is mainly about just getting it available to the customer. Sure we're the ones to ensure the availability, redundancy etc and help the organization get rid of mundane manual stuff but i never felt that sense of longing. @Jash Whats your take on this
Hi Jash, Nice and very informative video. Your consistency of quality is superb!!
I am from a service based company working as a DE. I can totally relate to the pain points in service based you were talking about, but that also makes it a thrilling job. Isn't it?
I learned today to continuously update myself in the technological aspect. Thanks for that.
Please continue bringing this quality content in the future as well!
Thanks Sanidhya! And yes, completely agree. These challenges make data engineering more interesting but some people might not be aware that they exist. Especially newbies. Thanks again though 😊
Yes, totally agree with you. Even I didn't know about these challenges when I joined and was a little bit frustrated, but as I am gaining experience, I am finding it more interesting and challenging. As you mentioned, we have to regularly communicate with our clients, this makes it an intriguing job.
@@sanidhyajoshi5619i sanidhya, i also work in service based company,I want to discuss something with you regarding DE,can I get your Gmail or contact
as a fellow data engg, working in service based company, i can relate with you. stress is high and WLB is low also pay is less :( we are literally treated as second class citizens and other people will not give us the same respect like SDEs get. also learning part is so much correct. i literally spend some extra hours everyday to learn new tools and tech that i dont get time to spend on other things. starting to regret in data space. its better to be frontend or backend engg who has great pay, respect, high wlb and most imp less learning than DE.
I feel for you brother. I respect data specialists. You are taking care of your family with your professional skills. Your family definitely is proud of you. Ignore all the negative feedback and constantly improve your skills.
Man I completely agree. Im still doing my 4th year and I got an internship in this company . They put me to face the client and expect me to know everything, its not even 3 months in this company. Everyday Im fucking stressed as hell . WLB is fucked . I hate this shit .
So is Data Engineer not something we should do? What area of data is best such as MLE, Data Scientist, Data Engineer, etc., or do you regret working in data itself?
Hi bro I am java developer one of MNC I am planning to switch data engineer role for better pay. What is your opinion switching SDE to DE is good or bad
That has not been my experience as a data engineer, I am getting the same and arguably little better pay as our software developers, and I am more respected as they often come to me and ask for help since I have learned the ins and outs of our data infrastructure so well. I also have less work and stress as I am in the backend and not expected to pump out products like the software engineers. WLB is the same though we all work and leave at the same time.
Very precise. By asking to fix the data sources you must rely on different team and if they are slow / unresponsive it may take months to get the results...
Yes, exactly!
Spot on from a fellow data engineer.
Hey Jash! I'm a recent high school graduate with a keen interest in pursuing a Computer Science or Information Technology course at an Indian engineering college. Before diving into college, I've decided to take a proactive approach by focusing on learning Java programming and Data Structures and Algorithms (DSA) first. I believe mastering these foundational concepts will provide me with a solid groundwork for my future studies. After gaining proficiency in Java and DSA, my goal is to explore the exciting fields of Data Science and Machine Learning. I'm eager to embark on this learning journey and would appreciate any guidance or advice on the best approach to achieve my goals.
Your approach is great. Just remember, DSA, SQL and Data Modeling are foundational blocks for any data role.
I'm trying to become a business analyst for a medium sized company and it seems like it's a hybrid of a regular business analyst and a data engineer/scientist (Knowledge of R, SQL, and other software was a requirement) and I think that's exactly what I want.
Great perspective Jash. You definitely laid out the important aspects of the job. One part you missed out was that in many companies you may have to be on call to help with pipeline break/fix if reports/dashboards cater to critical business functions and it is a thankless/low visibility job with nice pay. Google or top tech companies may have SRE teams but that may not be the case with non tech companies. So if you don’t like to do on call/break fixes then don’t be lured by the money. I recently left this field due to on call burnout and I work for a fortune 100 company. Good luck!
So true. Thanks for adding this!
as an aspiring data scientist this was very informative
Hi Jash Radia, I am From Nepal 🇳🇵. A 19 y/o boy having a curiosity to learn Data Science. Can you make a video on the courses that are available online for data science step-by-step. If you can !! It means a lot to us ❤
It is very well explained, thanks for your effort 👍
Thank you!
Thank you it was a great informative video, I would like to make a request to understand how a data engineer will approach a problem of the sql database if it has 40-50% is a legacy data and what approach you will take to document it in absence of any formal documents.
The Intro 🤣👌🏻 Very well made video!!! Great Job Jash... ✌🏻
Thank you! 😁
I can totally relate to this points.
Regarding scd type II, how do you explain them to users or business analysts. I had a lot of problems with analysts just using needless transformations to visualise such a tool, as opposed to giving them a long format table that they can visually transform easier. I know that a slider can solve the problem, but I found it that it can take more time to find the solution for them, than just give them what they want and accept my faith. Just curious
thanks buddy!!
I liked the topic about "being near and away from the business outcome" I am an ex - frontend developer doing master's in data science now. I have this same question for about 2 years now as I try to figure out my true interest in this big IT industry. So there are 4 factors -
1 salary,
2 significance (how close is our work to the business outcome),
3 dependency (how crucial is our work and to what degree can it drive the stakes),
4 work-life (+ how much can we delegate later in the career)
I do not want the best of all. But what I want is maximum value of this fraction: (salary * good work-life) ÷ (dependency or stakes). What role would allow me to maximize this fraction and where will I need to put the 2nd factor significance in this fraction? And somehow dependency and significance also affect number of jobs and their growth rate and salary growths too.
What would be the best role if you want the best optimal point from all the above factors? I will consider focusing on that role and it's tech stack and skills.
Did you got the answer?
@@overlord7096 yes. The answer to this question is that it was the wrong mindset to maximize this fraction. The world is vast, I'm going to explore what i feel is right and if there are many options then just pick the ones that pay the most unless they have some sort of a catch that can create a significant problem specifically for you.
really love your question and looking for the answer too :3
@@s0ulweaver What career path do you recommend?
@@scrotiemcboogerballs2133 tough question if you want a best personal answer. As of now, I'm going all in for data engineering. And my mental door is open for cloud as well while definitely shut for software development. But the software engineering exposure was worth it, I genuinely feel I have an edge in my learning curve for new technologies in data science as compared to others who directly came to data science. My personal recommendation would be start with data engineering (1st preference), cloud engineering (2nd preference), data analytics (3rd). Then after 3-5 years make data science as top priority with a decent know-how in cloud tech stack.
the amount of times i had talks with C-level managers expecting something like a datalake solving aaaall their analytical problems ... completely oblivious about it's not more than a tool .. enabling fast processing of large data amounts and grab and forget data collection .. but it's not providing value .. (yet) all the work has to be done anyways ..no matter which tool is used ..
I have been in Data space for more than 1.5 decades. My advice is, if u r not good in math, then pls pls dont go for DS. Bcoz I have been seeing so many primary school mistakes from Data scientists (those who have completed a DS course and claim that they are data scientists). Start ur career with DA/ DE, then parallelly build a good foundation in Math - then slowly switch to ML/AI... As of now, most of the Data scientists are just configuring the Black Boxes (ML algos) - not creating or contributing to the ML algos...
I m not kidding...
In an interview, I asked a guy to write the equation of a straight line and asked to explain it in simple words... Responses were awesome
Totally true 😅 maths without DS is like kayaking without pedals.
please make a video covering how to get job at good place with good package as a fresher,companies target,skills,interview prep and what mistakes we should avoid
Sure, thanks for suggestion. Will try to make a video around this.
which linux distro you recommend for DS,ML
@@zeusdelta2842 it doesn't matter. All distributions have ways to install commonly used packages.
@@JashRadia still i love to know your preference 😃
@@zeusdelta2842 I usually prefer Ubuntu then cent os. I avoid RHEL since it is expensive to licence.
Your skit at the beginning was funny. I am an ML Engineer who now works as a Data Engineer. So many people have no idea that the two roles are different things!
Ikr!
Hi Troy, I am also in the process of doing career shift from research ML engineer to Data engineer. As you already did you must be having some idea like pay wise both are equivalent or there is much difference?
@@AnilPawar-jy9sn That is a bit of a difficult question. Theoretically Data Engineers make more. However I took a minor pay cut to secure a job that is more likely to be recession proof and has a management track.
How to become ML engineer??
Hi Jash, thanks for providing such an informative source. Especially, the last part about tech tools transitions (Hadoop to Spark) blew my mind because I was about to take the Hadoop course for this spring semester! Now, I would like to ask you if Hadoop's skillset applies to Spark or Snowflake. If so, I'd keep my Hadoop course registration, otherwise, I'd drop it and will take the Spark course instead.
Thank you and yes. I would definitely recommend you to take the spark course instead of Hadoop. Yes you will find many things are common but most things are different. Better to learn spark in today's age. Learning snowflake can be done later since it is very easy.
Ok sounds great. Thank you so much for your advice!!
what bothers me the most is multiple tech stack doing the same thing, not getting fit because of it, and the job opportunities are still less.
Most projects in I have interviewd for in GCP end up using DataFlow(Apache beam) instead of Spark for distributed workloads. Could you please provide some usecase that can be used to have an actual hands-on witth spark or maybe some reference. I would want to apply for roles that use spark next. Thanks!
When you have more complex workflows with too many transformations, I would personally prefer spark over dataflow. I would prefer dataflow when there are templates I can readily use to move and easily transform data between 2 systems. In a typical high volume data processing platform, spark is better. Dataflow is more like a bridge that also supports smaller transformations
Can you comment on project pro.. Does it really help.. Does it have real time projects which industry uses, what did u feel personally and do you recommend it
I used to think Machine Learning was the brilliant thing in the world of data science, but after doing data science course i have great respect for Data engineers. ❤.
As an AI Engineer now, Couldn't agree more!
Hi jash, it's difficult to manage DE techstack, companies still don't understand what should they expect from employee, even in interviews they will ask OLTP, OLAP, Hadoop suite of applications, Spark, Snowflake, Databricks with any cloud services, even for them it becomes difficult to chose right candidate.
Yes true. It does get overwhelming. But key is to show that you are good at skills you know and show confidence that you will learn the rest.
Its funny that data engineers feel second class citizen when compared to managers n ds, truth being told all these data centric manager n technical roles have evolved after recent big data boom where companies wants to make most out the data that they have or wants third party company to help them with it. Guess what during the hard times it was these same roles or associated data product teams that were kicked out first, be it during covid pandemic or recent layoffs. If you really want secured n stable job in tech industry you better associate with tech stack onto which the core business runs 24*7, cool tech buzz might give shoot your salary up in corporate world in very short period but it can never ever guarantee stability.
Hi josh, thanks for your videos they're very informative and we appreciate the effort . In your Q/A video u mentionned hiw the second step after following the roadmap or acquiring the necessary skills would be to apply it through projects :as a DE student i find it hard to do that since it always seem too big of a task for a beginner/student . Are there websites or sources that contain projects ideas or guided ones either in DE or DS ?
Thank you! And for projects, yes it can be a little overwhelming but we have to narrow down our focus to one of 2 components while working instead of looking at the entire architecture. Project pro mentioned in this video is a great place which provides to guided projects. One more place is @DarshilParmar 's UA-cam (www.google.com/url?sa=t&source=web&rct=j&url=m.ua-cam.com/users/darshilparmar&ved=2ahUKEwjV5ejar9r8AhUz3jgGHfboDE8QFnoECBQQAQ&usg=AOvVaw3WkBfPxtYxTVvNo_SYkVzd) channel where he has about 4-5 projects he has solved.
@@JashRadia Thank you! I really appreciate it .
Another way to think about it is that DE's are the ones who actually deliver something whereas most of the work DS' do goes absolutely no where.
Yes because a lot of DS work is experimental tbh.
Very well explained brother🫡
all points I can relate 😅
Thank you! 😊
Great video
I worked as a Data Engineer for almost 3 years (Spark application development). I agree with most of the points here. Except few,
1. Data engineers usually have more work compared others like Business Analysts / Data Scientists during the application development.
2. Doing dev work in DE usually comes with some risk. Any bugs in your code has substantially bigger impact. You will be accountable for any errors in data processing. Also it is very difficult thing to track what caused the issue and since when.
3. Testing the correctness of application usually takes longer than other software systems.
Exactly
Thanks a lot Jash for the contents.
Can you put a highlight on the differences in the use cases of Dataframe transformations and spark SQL.
Welcome! And SparkSQL and DataFrames are basically your two options for doing those transformations. SparkSQL is just that, SQL-based transformations, the DataFrame option is more method and calls, more familiar to the programmers. It doesn't matter which one you use. It all comes down to preference of engineering teams
Hi Jash, I've been wanting to choose data science as a career and stumbled across your channel. It's been really amazing and informative learning from you. I am 20 years old in college and have already started learning python after watching your roadmap video. Anything I should be beware of for the future scope in this industry?
I have added some points about future of DE on my QnA video but apart from that, I can't think of anything else for now.
Edit: thank you for watching my videos and supporting the channel!
All valid points. In cost centers, or CoC, where you are not under the CIO organization, your direct lead is non technical person and you are limited to tools associated with no or limited cost, then you are Data Engineer without described harsh reality, its even worst, all is hyped to Data Science, no one want to invest time to data governance.
Yes, so true.
Hi jash...which cloud will create more data engg jobs going forward?
Then what are the jobs that fits into "go to starbucks and open up the laptop" profile??
If that makes you feel better: every employees are considered 2nd class citizens to executives.
More seriously, unless it's a tech company, all IT workers are considered 2nd class citizens.
Hi there, I am doing btech computer science from a teir 1.5 college but I have no interest in coding many if my friends have got a software engineer role in big banks like Deutsche and I'm thinking of getting an mba in finance from iim so will I be interior or superior to my engineering batchmates, n will I earn less or more on average, please answer, thanking you
Business request changes and so data request will change and complex business logic will have to be implemented. As far as I am concern No-Code Technologies can not meet the expectation of business 100%. There will still be some element of development and embedded coding
Yes, so true. It can improve but not to a point where you don't need any development effort.
Hi jash
Serious question
I am currently in support role
Wanted to switch my career to data engg.
I am avg in coding will it be suitable for me
Please answer as soon as possible.
I want to make this decision quickly
Completely Relatable Bro....
I landed a Data engineering Internship and I am hoping it turns into a job after I graduate. The company has been awesome far
All the best!
Please give me a link, thanks
How did you got the internship, can you please share ?
bro I also got internship for 6months. but they extended it for another 3 months. What abt you ?
You are my inspiration sir
Thank you, you are too kind!
I have total 8+ of years expereince in IT and I have more working expereince on sql and working exp of 3 yrs in informatica. Whaat do you suggest for me to learn new tech is it data engineer or devops is better ? Please suggest😢
I just found your channel. This is awesome. Can you do a top ten onlilne resources (free or not) for learning DEng?
Checkout the roadmap video on this channel for this.
Hi jash, missed the 2 hour mark but got a question. Is it better to focus on one thing of data engineering or to know everything a little bit for me to get a job. Please let me know since am starting a bootcamp in a few days :)
You can't learn everything but yes basic knowledge helps. Ultimately your goal should be to be an expert or a go to person in one domain. Be it spark or cloud or dwh etc.
Hi Jash, Thanks for the info. Which one is good for a Masters student in Data Science, Data Engineer or Data Scientist?
Data scientist. But gaining skills of DE will still be helpful
actually the first point is a good thing to me being a second class citizen because we don't have to face so much questions that the non technical stake holders ask and we work at the backend and we don't getting attention like the mle or ds get and also have a good pay
Yeah, exactly
Dude, spot on hahaha
Hey Jash! i'm shortlisted for the role as a btsa at zs associates. So just wanted to know if there are any similarities in the work that a btsa does to that of what a DE does. Thank you ❤
Congratulations! Yes there are so many similarities. Depending on your team your role will be 60-95% similar to a data engineer. Happy learning.
@@JashRadia Thank you so much for the reply sir
@@Jay-yu2jx no problem man! And no need for sir 😊
Thanks for the video Jash, I kinda stumbled in as a fresh data engineer myself, and I do believe I am going to stay. Hope we can connect.
Glad to know Daniel!
I'm really interested to become data engineer in future but I really dk which btech degree I choose to pursue first bcuz I'm not that good at studies so Cse degree will be hard but I can get IT or data science
Please help!! very confused now a days. Im mechanical engineer having 4 years of experience. I quit my job and learn Data analytics skills like powerBI, python,sql.. now someone suggest me go for DE . Great opportunity in future. DA job are less according to him.. wht can i do.please help. Should i starts learning DE? Or focus my existing skill for DA?
Hey great video, helpful information. I currently work as Data Scientist for 2 years, I thinking of exploring Data Engineer career path, what should be my initial learning in terms of technology or tool?
Bro I need job of Data Analyst entry level please help me
Thank you and Check out the data engineering roadmap video on my channel. It will answer your question and more.
Hey brother, I'm looking for internship in data engineer or ml engineer role in ahmedabad.
Do you know which companies hier data engineer in ahmedabad for internship and full time job?
For becoming a data engineer do we need to have good knowledge in maths or maths is very important would you clarify this please? Because I'm good at maths but I'm aspiring to become a data engineer and this is the drawback I have
You do need basic mathematics skills for any CS background field. But you don't need advanced maths in DE unlike in ML
How I can move from database developer to data engineer. With an experience of 3.5 yr in(database developer )
Hi Jash your explanation is so good it would be good if you make vedios regarding technical terms used like environment and types, dev test prod what does prod mean deployment mean and so on
And if possible please make vedios on simple projects
Thanks! Suggestion noted
Is it possible to get remote jobs in data engineering for freshers?
I was too late to see this video. still, I'm eligible to comment here! please suggest, when we should think move of data engineering jobs people who want to survive in IT 45 age+?
off-topic: dude what an epic t-shirt you have there. Nice!
Thank you 😁
Thanks much Jash for the details . Iam currently working as oracle dba in rotation shifts.Could you suggest some job with less coding skills
Data analyst is a good job with less coding skills
I have been working as Data scientist for 2 years but not getting much work on Data science things instead I get other things. Recently I started working on DE tools it caught my interest, was planning to switch from DS to DE
What are your suggestions?
It should be your choice but yes I have seen a few people make this switch if they are interested in more core tech work compared to DS.
I have begineer level of knowledge in Spark. I want to know from where I can prepare or solve interview related Spark questions. Can you provide suggestions for improving my spark skills and any websites or resources to practice?
Checkout my roadmap video on the channel. In the description, you will find resources that I recommend for learning spark well.
Hi Jash,I have five years of experience working as a data analyst, and last year I gained expertise in Snowflake and transitioned to a data engineering role. While I have intermediate SQL skills, I am currently struggling to understand and write complex SQL code. Can you provide suggestions for improving my SQL skills and what other technologies I should focus on?
In SQL, there are usually 20-30 types of queries. If you solve one and understand each type, you will be able to apply that knowledge in the rest of the queries.
Start with this: artoftesting.com/sql-queries-for-interview
And then practice from leetcode.
Also, try to create the tables and tranformations on paper before writing SQL in complex questions
Thanks for your response, I have intermediate level skills in Python programming language. Can you suggest other tools and technologies that I should learn and focus on to enhance my skill set?
Can you share your LinkedIn ID
I'm in 2nd yr and I'm able to solve medium-hard sql ques on Leetcode and stratascratch.... did some 100 python array string ques on gfg and Hackerrank.......
By the end of 3rd yr.....I will apply for data roles
Now I'm going to learn linux....
My question is :> Is AWS cloud practitioner certificate enough to work on projects..
I would suggest AWS solutions architect. You can skip the cloud practitioner one.
@@JashRadia okayyy thanku so much
I have a confusion, should I focus more on MySQL or PostgreSql ? I know that most of the syntax are same.
Doesn't matter. You should know one of them. I have seen postgres used a little more than MySQL though.
I have been a data analyst for 6 years now, current in a lead role, currently earning over 25 lpa (fixed). Have super high interest in this role but changing careers is pretty daunting. How much would does a DE role get paid for someone starting afresh?
What you mentioned is a good pay for a data analyst. But data engineers earn more than data analysts usually. In consulting firms, I have seen DEs being paid 35 lpa+ for YOE you mentioned and in good tech firms, it can go upto 70-80 lpa+ too. It can go even higher but those are super rare cases.
Jash i am interested in DE but i am in big confusion to choose this field.lot of people are going in to this and lot of are coming so it difficult to stay in this field for a longer period? .
No. I have seen many in this field for a long time. It is not difficult. People move and and out by their preferences
Hi Jash. I am a developer and currently I am confused to opt whether Data Engineering or Cloud Computing, Could you please tell which of these two has a better scope and salary in future.
My advice would be to learn cloud fundamentals anyway. Then you need to choose an area that you will work with. Eg, a full stack engineer, data engineer, data scientist etc. This is where you will start focusing more on a particular area. But anything you choose will eventually need atleast fundamental understanding of cloud.
Cloud computing is a subset of data engineering usually. Since most data engineers are cloud data engineers. Hence, they are also well paid compared to only cloud engineers.
Thank you Prasad and Jash🙏🏻
00:47 "we'll be using machine learning" perfect delivery LOL
Sir, would you please bring a video on the Data Engineering Role Hiring at Amazon through the Amazon WOW program, bring someone who would have been hired for the Data Engineer role at Amazon through Amazon WOW?
I'm sorry but I have no idea about this program or hiring at Amazon.
Can i get a data engineer certification instead of a college degree.
Need advice everyone
For someone who isn’t a big fan of coding, which role will be most suitable data analyst or data engineer (data scientist is coding algo heavy so not going that side)
Data Analyst, infact i will suggest business analytics
Hi @JashRadia Thank you for the videos. Im trying to find a course where we have a structured system design course which is sufficient for Sr DE interviews.
There is no perfect course for it. But you'll find a lot of UA-cam videos on it. Like mock system design interviews
You’re UA-cam channel is hidden gem for me .💎
Thank you! 😁