Sourav Ghosh @coder_91

Data Engineer | 4+ Years in Data Engineering | Building scalable ETL pipelines & cloud data platforms | Azure • Databricks • Spark • SQL Pune India Joined May 2018

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Sourav Ghosh @coder_91

3 weeks ago

@AiLearnersIndia Amazing 🔥🔥

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Piyush Sachdeva - Building ReelDrop + CannerAI 🚀 @techie_piyush

3 weeks ago

I don't like coding that is why I want to get into DevOps. This is the comment I get most of the times from students because people think DevOps/cloud related roles are about using no-code/gui based tools. It's hard to break this to you but that time is gone and never coming back Back in 2012, I started as an application support engineer at Accenture. When DevOps started picking up in 2013, everything felt mostly GUI-based in Jenkins. Click a checkbox, fill a text field, save, done. Then reality hit. Underneath the pretty UI, I had to write shell scripts. Then came Groovy, YAML, HCL for Terraform, and Python. When I interviewed at Google for a cloud engineer role, the toughest round was not about building an app from scratch. It was a code troubleshooting round. No IDE, no editor, just a document and my voice explaining line by line what the code did and finding the hidden bugs. That changed how I look at DevOps. You are not the application developer. You are the maintainer. Once the developer hands off the code, you own the path from UAT to production. You cannot maintain or debug complex systems at 3 AM if you cannot read and understand code. AI handles the raw typing now, but reading, reviewing, and understanding code matters more than ever. The 6 core technical skills needed for DevOps: → Linux and Shell Scripting → One core language like Python or Go → Configuration languages like YAML, HCL, and JSON → Basic data structures like lists, dictionaries, and nested JSON → Reading and debugging existing code → SDLC and Git workflows If you are trying to learn DevOps, do not try to master everything at once. Pick one language, get comfortable reading code, and build from there. Watch the detailed video (link in the below comments)

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Sourav Ghosh @coder_91

3 weeks ago

Success that cost you your peace is a deal lost ! #success #goals

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Sourav Ghosh @coder_91

a month ago

@swstica @dimensionalos github.com/souravghosh251

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Sourav Ghosh @coder_91

a month ago

2 PR's successfully merged on @corsairdotdev 🚀 Small contributions, but a big step forward in my open-source journey. github.com/corsairdev/cor… github.com/corsairdev/cor… #OpenSource #GitHub #SoftwareEngineering

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takeUforward @takeUforward_

a month ago

You can literally comeback from everything. It's all about mindset.

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scar @imfat

2 months ago

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Dear Son. @DearS_o_n

2 months ago

Kill the nice guy inside you and become ruthless. Life is rough to men out here.

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Dear Son. @DearS_o_n

2 months ago

Dear son,

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Sourav Ghosh @coder_91

2 months ago

Technical skills can be taught. But discipline and patience? That has to be earned. It comes from failures. From experience. From realizing that no one is coming to save you. #latenightthoughts #discipline

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Mindful Maven @mindfulmaven_

2 months ago

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The Sigma Mindset @thesigmamindset

2 months ago

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Sourav Ghosh @coder_91

2 months ago

Real!

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Dear Self. @Dearme2_

2 months ago

Bro talk,

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Sourav Ghosh @coder_91

2 months ago

Learn SQL. Learn Python. Learn PySpark. You’ll become a Data Engineer. ❌ Understand why, when, and how to use these tools to solve real data problems. That’s what makes you a Data Engineer. ✅

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Dear Self. @Dearme2_

2 months ago

I’m getting a car this year. Repost if you believe

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Gary Vaynerchuk @garyvee

2 months ago

The fear of judgment and losing is what is paralyzing you. Make a decision. Take action.

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Sourav Ghosh @coder_91

2 months ago

Most people think Data Engineering is all about tools! But in reality, it’s about solving problems. The requirements decide the architecture, and the architecture decides the tools. Don’t start with: “Which tool should I learn?” Start with: “What problem am I solving?”

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Arpit Bhayani @arpit_bhayani

2 months ago

Our only unfair advantage left is wondering. Not knowing. Not having the answer. Just being curious enough to ask, "What if?" Machines are getting better at knowing. They are getting better at finding answers, connecting ideas, and even producing things we once needed years to learn. Perhaps our advantage is not in knowing more, but in knowing what is worth wondering about.

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Striver | Building takeUforward @striver_79

8 months ago

Just checked: in the last 6 months, they have tried a few AI products (possibly the reason). When most candidates prepare for skill ‘X’, it’s difficult to convince a company to hire for skill ‘Y’. The company that does it will lose out on the talent. As you stated in one of your tweets, you did DSA just to get into any company. So as a company, if I ask you to do something different, you won’t put in the time to learn and appear (unless it’s a Google or a big fat salary is offered). Anything that involves just AI and not fundamentals, in my opinion, will have higher false positives, making hiring extremely difficult.