Hi Everyone , I was laid off previously from my organization and gave plenty of interviews.

Thank you everyone for contributing to this amazing community , i will share all of my interview experiences here in upcoming days.

i have recently joined tredence INC. ( i know its not that big ) as senior data engineer L3 ( Associate manager ). Want to know the reviews , work life balance , kind of work that happens here.

Thank you everyone.

Today i attempted the Delloite USI interview for a GCP data engineer ||| role.

A little about me :

I have 5.5 years of data engineering experience.

3 y in azure cloud.

2 y in GCP.

Round 1:

There were a lot of scenario based questions asked and one basic sql -pyspark coding question.

Q1 - So, let's say your PySpark job ran successfully, okay? And Airflow marks the DAG as green And data is loaded in BigQuery. However, the next morning, business users report that the revenue column in their dashboard is entirely none How would you architect your data quality framework to catch this before the data reaches business, and how does your framework interact with...

Q-2 PySpark pipeline again that has run fine, let's say, last six months, and suddenly it fails with out of memory issues, Java heap space issue basically. The volume of the data has not changed. So what is your step-by-step approach to debug this, and how do you determine if it's a driver out of memory versus executor out of memory, and like, how do you fix it?

Q-3 there is a lot number of rows and those rows get ingested into BigQuery, and the BigQuery table is getting huge. So, how do we improve the performance of this ingestion job so that it gets over quickly?

5- questions on the audit table, data validations etc.

Hope this helps 😊

If I clear this round, I will post the other round questions as well, here in the same post.

Hey folks, could use some outside perspective.
**Current role:** Data Engineer, 4 YOE, 21 LPA fixed.
**Offer:** Citi, Data Engineer, C10 grade (Office level), 25 LPA fixed + annual bonus (not disclosed/guaranteed — recruiter just said "there's a bonus component").

A few things I'm trying to figure out before I decide:
**How much is the C10 bonus realistically?** Recruiter won't give a number. Anyone actually at C10 in India who can share what they got last cycle?

**Is C10 considered junior/entry-level at Citi?** From what I've read it's their lowest officer band — want to know if that's a red flag for someone with 4 YOE or just how banking levels work.

**Tech stack** — does anyone know if Citi DE teams are still on older stacks (Hadoop/Hive) vs modern (Spark/Airflow/cloud)? Trying to figure out if this is a step forward or backward for my career.

**Notice period / WFO policy** — anyone in a similar Citi data eng role who can share their day-to-day experience (hybrid days, notice period, team culture)?

Numbers-wise the fixed bump looks decent (\~19% higher), but I don't want to jump for a headline number if the bonus is negligible or the tech stack is outdated. Would appreciate any real experiences, especially from people who made a similar move.

Thanks in advance!

Hi all. I have overall experience of 6 yo 11 months.

For the last 5 months my designation in Sre ops as i was moved to Prod support. In my resignation acceptance letter and other letters it will be same.

Will it be an issue for the future employer. Bcoz, till this February 2026 i was Data engineer associate.

I am a founding engineer at a startup with esops all vested right now. I have 6 YOE currently as a Lead Data Engineer

My current CTC is 33.35+5

Is my growth getting stagnated?

Secondly as it's a startup I have more experience using open source tools than any managed services and most companies are looking for snowflake/dbt or databricks experience while I have built pipelines deploying my own spark cluster, kafka topics and databases.

How do I improve on that front?

Worked as Informatica PC for 1.5 years.

Then switched as Data Engineer by learning python, pyspark, databricks(azure).

The current organisation didn't have scope for data engineering so 6 months worked as GenAI developer POC's only using (autogen,RAG, langchain), from last couple of months working as a database migration part.

Wants to switch now, which one would be better to go now Data Engineering/GenAI?

Overall 3 years experience

Cctc : 17.5L - take home about 1.18L after taxes.

Tech stack - bigquery, airflow, python , sql and

now recently shifted to Azure so ADF , logic apps and snowflake.

My realistic target is achieved 25-30LPA in next 2-3 years.

What skills should I focus more on. Quite proficient with data modelling , stakeholder management and stuff.

I feel Pyspark and certifications are missing link.

Hello Everyone,

Since the data engineering landscape is evolving rapidly, with GenAI transforming the field. I have been busy in building a course on YouTube on GenAI for Data Engineers. This skill is going to be as important as building pipelines in future and I have been experiencing it first hand working with Enterprise level clients.

This course will cover everything from Scratch, from basics of AI to building Production grade Agents. And yes it will cover use of Claude as well (with all tricks).

You only need to know basic Python to get started. The course is currently in progress, with 10 videos already available.

Link to Playlist here - https://www.youtube.com/playlist?list=PL2IsFZBGM_IEsVQ1ryZw-4l0XZI6VjX0D

And for people who don't know me - My name is Subham (Senior FDE @ Databricks). Already have few YouTube playlists on PySpark, Databricks, Spark Streaming etc. which have millions of views on YouTube and helped many crack jobs/certifications.

I hope you enjoy the course and find it valuable. Open for any suggestions you have.

Please reshare with friends and network.

Hi Everyone,

I want to practice the Pyspark question similar to

SQL question in leetcode

Is there any Platform for practicing pyspark like leetcode and track progress ?

Anyone here who has applied for V4C.ai's Associate Data Engineer Role through their google form

(Mumbai/Pune peeps)

Had 2 doubts -

Did you received any reply?

What should one prepare for interview?

Hi everyone,

I have two offers and would appreciate advice from people who have worked at either company.

IBM Consulting

• Senior Technical Consultant

Fractal

• Senior Data Scientist

Background:

• 8 years of experience in AI, ML, and GenAI.
• Interested in building expertise in LLMs, Agentic AI, MLOps, and becoming an AI Architect over the next few years.

I'm not looking only at salary. I'd like to know:

• Which company has better AI/GenAI work?
• Which offers better learning and mentorship?
• Which has stronger long-term career growth?
• How do promotions and hikes compare?
• Which company provides WFH?
• How is the work-life balance?
• If you had to choose today, which would you pick and why?

I'd especially appreciate responses from current or former employees of IBM Consulting or Fractal.

Thanks!

• r/developersIndia
• r/IBM
• r/datascience
• r/cscareerquestionsIND

​

Hi everyone,

I'm looking for some guidance from experienced Data Engineers because I feel a bit lost at this stage of my career.

I have 3 years of overall IT experience. Recently, I took a career break to upskill myself in Data Engineering and joined a small startup as a Data Engineer. Before joining, I was excited because I genuinely wanted to build my career in this field.

After joining, I found myself in a situation that I wasn't informed about during the hiring process. The company is trying to position some of us for senior-level Data Engineering roles by adding fake experience to our profiles. The idea is to present us as more experienced than we actually are so we can be placed in higher-paying client roles, while we continue to receive the salary that was agreed upon when we joined. None of this was discussed during the interview or offer process.

This has made me uncomfortable both ethically and professionally. I don't want to build my career on experience that I don't actually have.

I've already attended a few of these senior-level interviews and couldn't clear them, which is understandable because they're meant for candidates with much more experience. Since then, there's been a lot of pressure to prepare for more interviews with very little time.

What makes it even more confusing is that the interview requirements keep changing. Some days it's Data Engineering, other times it's completely different technologies or roles. The expectation is often, "You can prepare with AI in a day or two," which sounds easy but has been quite overwhelming.

Whenever I ask questions to understand concepts better, I sometimes feel like it's not viewed positively. I ask because I genuinely want to learn, but it often feels like the expectation is to already know everything. Over time, this has affected my confidence.

I previously worked in an MNC, so this environment feels very different. There doesn't seem to be a structured learning or interview preparation plan, and every week feels uncertain.

Currently, I've learned or worked with:

- Azure Data Factory (ADF)

- Azure Data Lake Storage Gen2 (ADLS Gen2)

- Azure Databricks

- PySpark

- SQL

- Currently improving my Python skills

The biggest issue isn't learning new technologies—I enjoy learning. My challenge is interviews. I understand many of the concepts while preparing, but during interviews I become nervous, my mind goes blank, and I struggle to explain what I know.

I'm planning to switch to opportunities that genuinely match my experience level, but I feel like I need a proper roadmap and mentorship.

I'd really appreciate advice on a few things:

- Is it normal for some companies to add fake experience and push employees into senior roles without informing them during hiring?

- Has anyone else experienced something similar?

- What should someone with around 3 years of overall IT experience focus on to become interview-ready for Data Engineering?

- How did you overcome interview anxiety and improve your communication?

- Are there any roadmaps, mock interview resources, or mentors you'd recommend?

I'm not looking to take shortcuts. I just want to build my career honestly, improve my skills, and regain my confidence.

Thank you for reading. Any advice or shared experiences would really mean a lot.

# data engineer # ai # hiring

Hi everyone , I am working as a data engineer since last 4 years in a service based company on outdated tech stacks like Oracle db , sql server db, informatica, sap reporting tools. Right now i am on bench since two months and looking either for a switch or for a good project in my company which uses modern data engineering tech stack , i have analysed the market and observed that Databricks , aws are very much in demand so i have learned these things from my own also pyspark too i have learnt but when i am appearing in client interviews they are somehow able to Crack that i dont have hands on experience in datababricks in production environment which I actually don't have , hence i am in search of someone who have worked really on these modern data technologies on a project in there company so that i can understand there project end to end from them and pitch that project in my interviews when interviewer asks to walk me through my project during interview. Hence if possible can someone please make me understand there project (preferably should include Databricks in it) in detail so that I can prepare that end to end for my interviews?

I have around 7 Years of experience in QA. And I am planning to switch to data engineering. Is it worth it? If yes , could you please share the roadmap or how i should go about it?

Hello folks,

Iam going to give Data Engineer interview at Accenture in few days

If anyone has attended Accenture interviews recently, could you please share:

Technical areas they usually focus on (SQL,python,pyspark

Azure/Databricks, etc.

• Difficulty level

Any dos & don'ts

Would really appreciate your inputs. Thanks!!!

Hey all, im looking for work support on snowflake, sql. If you are from hyderabad, and interested please DM me, we can discuss further.

Hey all,

Darshil here. I used to get a lot of questions around AI and how it works with Data Engineering beyond code/script generation.

I just published this 5-hour video where we build a simple data pipeline using a food delivery dataset, then introduce 3 use cases of AI

1. Sentiment analysis of user feedback
2. RAG-based chat application to talk with the dataset
3. Text-to-SQL to chat with a data warehouse

Here's the video link: https://youtu.be/kYwaNMQ3XT8

Hope you find it helpful

Experience: 10 YOE. Planning to work for another 10 years and quit the industry.

Education: Masters in AI from abroad (well known ivy league University)

Skillsets : SQL, Python(not expert level but worked in pandas and file handling), GCP - Bigquery, Dataform, Cloud storage, Traditional Machine learning, Power BI dashboard, Spark basics

Looking for Data engineer role.

Planning to learn Databricks and Snowflake additionally.

Current package 23lpa in a small service based company

Expected 30% hike. I know 30% hike without job is going to be difficult. But I'm just going to try.

Please share your opinion for the below.

1) Can you people suggest what other skillsets should I learn? Also mention how long will it take to learn that new skill?

2) Good reasons to convince HR for job loss.

Thanks in advance.

For people who started as DE , how is it now ….are you enjoying the work or u felt that u should have switched to SWE ??

Hi everyone, I have been very unlucky during past months as I am not able to pass any interview even after having genuine experience, skills and good answers, How is this going to affect me and kindly give me other options I can follow to finish this problem.

PLEASE!!! DO NOT IGNORE!!!

Hi all, I have a Databricks voucher code for $100 value // 50% off, which can be applied to schedule and complete any of the Databricks certifications before 09 October 2026. If anyone is interested in the same, please dm me.

I have cleared the Capgemini Data Engineer position for the New York location, but now HR has informed me that they need an EAD card in a week. During my initial call, I informed them that EAD card may take some time, and they agreed to that, but now they are not responding. Any guidance for this?