Amit kumar

Last week, I got a call from the CEO of the startup I joined 6 months ago. Everything was good. I had shipped 25+ PRs, built 40+ reusable components from scratch, and fixed end-user bugs within a day. I loved the team. I loved the product. It was finally the kind of place I had been chasing since my first year at IIT Bombay. Then he told me the funding round didn't come through. No runway left. So no job either. I'm not going to pretend I took it well. I sat with it for a few days. It's a strange kind of grief; nothing went wrong, the work was good, the people were good, the product was good. The bank account just didn't grow fast enough. I'm 22. Just graduated from IIT Bombay this year. No savings to coast on. I need to figure out what's next in the next few weeks, not the next few months. So I'm doing the thing I've been avoiding. Asking for help in public. What I bring: → Frontend engineer, ~1 year shipping production code → React, TypeScript, Next.js, Node, Python, Postgres → Built and launched my own SaaS products end to end → Comfortable being the first or second engineer at an early-stage startup → Move fast, don't need hand-holding What I'm looking for: → Founding / early engineer role at a startup, actually building something real → Remote or relocating, both fine → Can hop on a call this week If you're hiring, or you know someone who is, please reply or DM. Even a repost would mean more than you know right now.

@F89014Uche Stored procedures or postgres function failing with one line message and then trying to understand which part of 800-1000 sql script caused that ,🥹

99% of Data Engineering: Reading logs Googling errors Pretending everything is under control 😂

@byte_array That's great to hear ,so basically we can get store,process, do modelling over data all in one place

Blog link: onehouse.ai/blog/real-apac…

It’s snowing in the San Francisco summer.. Most companies offload their Snowflake ETLs to spark; We launched Quanton on Snowflake. So, you can finally run real cutting-edge Apache Spark, inside Snowflake.. For the what, how, why: checkout Kyle Weller ‘s blog here 👉 onehouse.ai/blog/real-apac…

@F89014Uche Sure, let's stay connected and keep sharing our learnings.

@Amit_official97 Thanks a lot for sharing your journey, Amit! It’s really encouraging to hear how you transitioned into AWS from a non CS background. I’m currently focused on learning SQL and PySpark, and I hope that once I’m done, I’ll get the chance to work with you someday.

Which cloud platform is best for a beginner in Data Engineering? 🔹 Azure 🔹 AWS 🔹 GCP I'm learning SQL and PySpark and would love to hear your recommendations. #DataEngineering #CloudComputing

@F89014Uche Actually I am from a non cs background so in mtech I started with python and then I got my first opportunity and there they were using AWS so that's how I started, in my current organisation I work on AWS mainly but some legacy pipelines run on ADF too ,so some exposure there.

@Amit_official97 Awesome! I'm considering Azure and AWS at the moment. What made you choose AWS when you started?

@akkiex007 But those there for the mission will still continue but a bigger question could be after listing if someone wants to join them how they differentiate then who are coming for money and who for mission , will that even matter or for now does it matter to companies like this?

I assume a lot of Anthropic employees aren’t there purely for the money. Many are probably there for the mission, the research and the opportunity to shape AI. Or maybe they’re there for the money too What’s interesting is what happens when Anthropic goes public. A meaningful number of employees could suddenly find themselves financially set for life. NVIDIA managed to navigate that because of its scale, Anthropic, on the other hand, operates with much leaner teams. It wouldn’t surprise me if they eventually face a very unusual retention challenge: employees leaving not because they’re unhappy, but because they simply no longer need to work.

@LinkedInHelp will you guys update?

So was it delayed tactics you guys tried @Linked

@LinkedInHelp please tell,I am sure I have not deleted any post ,why will I delete my efforts and now no one is contacting me. I request again please help me with recovery of my posts especially all the original ones written by me of my domain that is data engineering.

@LinkedInHelp Your team members came and said that my posts are deleted which I did not and they said my posts can't be recovered, I got this mail in morning IST ,I replied it almost 12 hrs back,they asked my contact no to discuss but haven't received any call ,so what to do now @Linke

@Amit_official97 Thanks for your prompt response and rest assured, we will try our best to assist you. I have replied you in DM with an update regarding your issue, please check it there. Thanks!-SY twitter.com/messages/compo…

@LinkedIn you guys decide to put my account on hold ,I updated all the documents you asked for still all my old posts are removed,my email updates, notification regarding different things like job application or comments and reactions on my post all has stopped and no support.

@system_monarch The most important point if everything is taken care by AI then will it take the ownership too 🤔.

“Cut every engineer who is not at 100% AI output” is exactly how companies end up with code nobody understands and outages that take days to fix. It’s funny because these hot takes blindly miss the point. A software engineer does not do one kind of work all day. Sometimes they write boilerplate. Sometimes they write tests, refactor old code, generate docs. AI can absolutely help here, do it even 10-20x faster. But sometimes they are designing a payment flow, debugging a production incident, or figuring out why a small edge case can corrupt data for thousands of users. That is not the same work. The impact is largely different. That's why teams should not measure engineers by how much code AI wrote for them. They should measure whether engineers used AI in the right place, understood the output, and owned the consequences after shipping. I would even argue that, an engineer avoiding AI completely is a problem. But, an engineer trusting AI blindly is a bigger problem. Because AI can sound confident while making the wrong abstraction. It can generate 600 lines for a 60-line problem. It can miss business context, ignore old system behavior, and create bugs that only show up under real traffic. And then someone still has to debug it. Someone still has to explain it. Someone still has to take responsibility when customers are blocked. I use AI heavily, but I don't surrender my judgment to it. As an engineer, you need to know when to ask AI for speed and when to slow down and think. It's only huge consequences if you don't draw that boundary.

@system_monarch Thanks

@Amit_official97 atlassian.com/blog/how-we-bu… Take a look at this Engineering blog written by me to get a glimpse.

As a Software Engineer with over 12 years of experience, here are the key technologies and tools I’ve worked with and recommend mastering: Databases +Relational: MySQL, PostgreSQL, SQLite +NoSQL: MongoDB, DynamoDB, Cassandra +Distributed SQL: TitanDB Messaging & Streaming +RabbitMQ +Apache Kafka +Apache Flink In-Memory Stores & Caching +Redis +Memcached Containerization & Orchestration +Docker +Kubernetes (K8s) Operating Systems +Linux (daily driver for development and deployment) Programming & Scripting Languages +C +Java/Spring +Bash +JavaScript (JS) +Web Development +React Project & Workflow Tools +JIRA +Confluence Monitoring & Logging +Prometheus +Grafana +ELK Stack (Elasticsearch, Logstash, Kibana) +CloudWatch CI/CD & DevOps Tools +GitHub Actions +Jenkins +GitLab CI +Azure DevOps +Terraform +Ansible +Azure Templates +Helm Cloud Platforms +AWS (EC2, S3, Lambda, RDS, DynamoDB, CloudWatch, EKS) +Azure (Functions, App Services, Cosmos DB, DNS)

@system_monarch As a data engineer I have worked with it in one project but the data stream velocity and volume that you might have encountered at Atlassian or any such big firms ,so an insight would help a lot . 2/2.

@system_monarch Hey Puneet, since you have worked with Flink as well as message queues,can you give some of its use cases with explanation in detail and how do you especially handle the state handling with high velocity data streams and the late arriving data part. 1/2.

@akkiex007 That's so diversified.

Busy week ahead, ~25 recruiter screenings. What’s changed from Q1 is the diversity of conversations. The calendar now includes Software Engineers across India & Europe, Engineering Managers, Data Engineers, Workday specialists and even Transfer Pricing professionals. I feel sorry for my average recruiter brain trying to keep up with so many domains, technologies and business functions, it’s switching contexts harder than a software engineer with 37 browser tabs open. One moment it’s distributed systems, the next it’s international tax structures.

Monday morning learning topic:-

@sumit_codes_ 🙏

@Amit_official97 We build together. We grow together

We have entered the month of June. What are your goals for this month? Mine is to reach 300 verified followers by the end of this month. If you don't know me, I'm Sumit a Senior Data Engineer helping out people to get better paying jobs in data engineering. Want to know how? Check the link in my profile. Here are today's stats at the start of the day.

@ishaangtwt @akkiex007 Yeah it is

@akkiex007 @Amit_official97 i'm not sure if this is satire

Is this true @akkiex007 ?

@chintanpuggalok @akkiex007 Yeah actually that's what Akash was trying to say , it's fine to have that.

@akkiex007 @Amit_official97 why is it a blunder? I have gotten inbound hiring offers just because of the open to work when I was looking to switch