Uploading after a while! These are 7 hard truths you need to face if you're learning about data engineering. GFG Premium: gfgcdn.com/tu/T9z/ Thank you for watching! Let's talk more about it here 😃
Hey,Jash This is Aryaman Singla I started following you recently and It is remarkable the way you are enlightening by sharing your knowledge and experiences , I have just got an offer as Data engineer at an analytics company and just starting my career as fresher. What top 5 things I should remember to grow in my career?
Hey Aryaman, congrats on your offer 🎊 and thank you for watching my videos! I would recommend to 1 stay curious and keep learning 2 take feedback positively instead of being defensive 3 work on high visibility stuff in front of leadership., overall that's best for career progression. All the best!
Hey Jash, Thanks for a wonderful video as always😃!! Any quick tips/suggestions for myself who is going to attend a Google DE interview in 3 weeks. Would love to hear your advice/thoughts
Practice solving leetcode easy, medium problems and focus on HLD about data pipelines. Also non functional components like observability,etc. More importantly, be confident and communicate well in all round. Focus on data modeling, too.
Hi Jash, I'm about to start my journey for Data Engineer. Thanks for organising my study plan i will try my best to stick to these 7 rules. Could you please suggest any best place where i can practise unlimited problems on python language please........
Start with leetcode.com/studyplan/top-interview-150/ You don't need to solve unlimited problems. Just focus on solving about 100. Patterns will start repeating then.
Hello Jash, Your content is really helpful. For someone who is starting as a fresher in DE,will it be difficult to stay in the job market after 5 or 10 yrs, due to automation with AI. Can you please suggest few skills that will help to stand out.
Hey Jash, considering where the whole industry is going towards, do you think learning AI tools would become a necessity for Data Engineers to learn and adapt? Great video as always!
Yes 100%. Learning prompt engineering well is now like learning SQL 10 years ago. Basics of gen AI is important. In fact, I am planning to make a video on this soon. Thank you!
Hey in the upcoming years will there be openings for data engineer role to freshers?? I have been said by many tht freshers aren't hired for data engineer roles but the same freshers can get hired as engineer in web development domain . So would u suggest me to build skills related to web development or data engineering
Create a simple project that helps answer a business question from data. Build a pipeline. End result can be in the form of dashboard, or a chat bot byilt frok AI which uses the data you just processed. It's ont of the ideas.
Why do people think it's the job profile. Many data engineers make more than data scientist and many data scientists make more than data engineers. It depends on the company and qualifications.
Is SDE Better than DE in terms of Salary Growth and Career Opportunities and Are there more job openings for SDEs as Compared to DEs? And can DE transition into SDE such as Backend or Cloud/Devops Profile later in career ? Also Can freelance Work Be done in Data field ? If Yes Please make a video about it. Thanks
Okay, just to clear out any doubts. SDE is the parent job profile. An SDE or SWE can be data engineer, full stack engineer, ai engineer, ml engineer etc. And yes DE can change to backend engineer and vice versa.
I believe data engineering can be largely automated with AI technology. In the long run, this could reduce the demand for traditional data engineering roles, while data science may see more AI-oriented tasks. For example, traditional pipelines could be shifted towards LLM-based models. This is my perspective; is it accurate?
Yes. Prompt engineering will be like SQL.. yes, AI will be in all aspect on DE and it will automated a lot of things we do today. What DE does will merge with AI a lot. It's just the evolution of tech. Things that were manual 50 years ago are automatic now but that doesn't mean there aren't new things to work on and innovate more on. Same will happen in future.
Not possible in the next 20-30 years!!! May be ai can code it for you but it will not be able to maintain a system!!! Companies like Google or meta can afford that kind of infrastructure but not every company can afford the huge infra costs. So DE's will be required to process data with max accuracy and with less infra costs!! These are some aspects where ai won't be mature. So if ai will tell to process data using a spark cluster having 1000 of nodes for some minimal Computation then it would be blunder right?!!
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Uploading after a while! These are 7 hard truths you need to face if you're learning about data engineering. GFG Premium: gfgcdn.com/tu/T9z/
Thank you for watching! Let's talk more about it here 😃
People are asking now for uploading your videos playing Table hehe thanks for the valuable videos Jash! Always a pleasure to watch.
1:16 some random senior data engineers getting bored: let's make a new tool
😂
Powerful message by this video.. "Doing is Learning." 😅😍👍🏻
💯💯
Very informative! Loved the point where you were talking about revision and how setting realistic goals can help us 😊
Thank you!
Great Video, Once Again ☑️👌🏻
Packed with Knowledge 👏🏼
Thank you
Hey,Jash This is Aryaman Singla I started following you recently and It is remarkable the way you are enlightening by sharing your knowledge and experiences ,
I have just got an offer as Data engineer at an analytics company and just starting my career as fresher.
What top 5 things I should remember to grow in my career?
Hey Aryaman, congrats on your offer 🎊 and thank you for watching my videos! I would recommend to
1 stay curious and keep learning
2 take feedback positively instead of being defensive
3 work on high visibility stuff in front of leadership., overall that's best for career progression.
All the best!
Is it possible to switch to data engineering role in service based company after 3 years of experience in Mainframe
Hey Jash, Thanks for a wonderful video as always😃!!
Any quick tips/suggestions for myself who is going to attend a Google DE interview in 3 weeks. Would love to hear your advice/thoughts
Practice solving leetcode easy, medium problems and focus on HLD about data pipelines. Also non functional components like observability,etc. More importantly, be confident and communicate well in all round. Focus on data modeling, too.
Hi Jash, I'm about to start my journey for Data Engineer. Thanks for organising my study plan i will try my best to stick to these 7 rules. Could you please suggest any best place where i can practise unlimited problems on python language please........
Start with leetcode.com/studyplan/top-interview-150/
You don't need to solve unlimited problems. Just focus on solving about 100. Patterns will start repeating then.
Hello Jash, Your content is really helpful.
For someone who is starting as a fresher in DE,will it be difficult to stay in the job market after 5 or 10 yrs, due to automation with AI. Can you please suggest few skills that will help to stand out.
Hey Jash, considering where the whole industry is going towards, do you think learning AI tools would become a necessity for Data Engineers to learn and adapt? Great video as always!
Yes 100%. Learning prompt engineering well is now like learning SQL 10 years ago. Basics of gen AI is important. In fact, I am planning to make a video on this soon. Thank you!
Hey in the upcoming years will there be openings for data engineer role to freshers?? I have been said by many tht freshers aren't hired for data engineer roles but the same freshers can get hired as engineer in web development domain . So would u suggest me to build skills related to web development or data engineering
what kind of projects to do for fresher trying to enter this field
Create a simple project that helps answer a business question from data. Build a pipeline. End result can be in the form of dashboard, or a chat bot byilt frok AI which uses the data you just processed. It's ont of the ideas.
@@JashRadia thank you
Can you please create a video on Data Engineering related books
sir, please help on resources for system design for data engineering..
What will make more money, data science or data engineering, please mention books.
Why do people think it's the job profile. Many data engineers make more than data scientist and many data scientists make more than data engineers. It depends on the company and qualifications.
Is SDE Better than DE in terms of Salary Growth and Career Opportunities and Are there more job openings for SDEs as Compared to DEs? And can DE transition into SDE such as Backend or Cloud/Devops Profile later in career ? Also Can freelance Work Be done in Data field ? If Yes Please make a video about it.
Thanks
Okay, just to clear out any doubts. SDE is the parent job profile. An SDE or SWE can be data engineer, full stack engineer, ai engineer, ml engineer etc.
And yes DE can change to backend engineer and vice versa.
Hey jash, I'm working as a data engineer and want to learn AI please make a video on this
Sure, thanks for the suggestion
Sir I want a job as a data engineer. Can u refer me or guide me. Help would be Highly appreciated
I believe data engineering can be largely automated with AI technology. In the long run, this could reduce the demand for traditional data engineering roles, while data science may see more AI-oriented tasks. For example, traditional pipelines could be shifted towards LLM-based models. This is my perspective; is it accurate?
Yes. Prompt engineering will be like SQL.. yes, AI will be in all aspect on DE and it will automated a lot of things we do today. What DE does will merge with AI a lot.
It's just the evolution of tech. Things that were manual 50 years ago are automatic now but that doesn't mean there aren't new things to work on and innovate more on. Same will happen in future.
Not possible in the next 20-30 years!!! May be ai can code it for you but it will not be able to maintain a system!!! Companies like Google or meta can afford that kind of infrastructure but not every company can afford the huge infra costs. So DE's will be required to process data with max accuracy and with less infra costs!! These are some aspects where ai won't be mature. So if ai will tell to process data using a spark cluster having 1000 of nodes for some minimal Computation then it would be blunder right?!!