Career growth rarely comes from one big move.
It comes from showing up every day — even when no one is watching.

• Learn when it’s boring
• Practice when progress feels slow
• Stay consistent when results aren’t visible

Perseverance compounds quietly.

If you can stay disciplined for long enough,
your career will look very different by the end of 2026.

No hacks.
No shortcuts.
Just consistency.🔥

🚨 My FIRST YouTube Short is LIVE! 🚨

This one is about a simple SQL habit that can save you from serious data loss in production 👀

👉 Before you ever run a DELETE, make sure you’re doing this one thing.

🎥 Watch here:
👉 One DELETE mistake can destroy your data 😬 | SQL
https://youtube.com/shorts/6AK2S2Qv5kU

If you’ve ever worked with real databases, this is a must-watch.
Drop a 👍 or comment on YouTube if it helped you — it really supports the channel.

More real-world SQL Shorts coming soon 🔥

Happy long weekend to all 🔥🔥
Use this weekend to relax and upskill yourself

Hey Data Engineers

One individual from this community just had an Snowflake DBT interview with TCS,these are the main questions asked into him

Snowflake + dbt interview questions asked at TCS 👇

These are not beginner-level questions — they test real production understanding.

• Difference between Snowpipe vs COPY INTO
• Can you clone a subset of a table in Snowflake?
• Track column value changes (Apple → Orange) using Streams + MERGE
• Types of views in Snowflake and their use cases
• What is CLUSTER BY and how many columns should be used?

• Is a Stream a database object in Snowflake?
•How do you register a source in dbt?
• Difference between external table and managed tables in snowflake?

https://www.linkedin.com/posts/adityabansal095_a-friend-of-mine-recently-interviewed-at-activity-7420836271784321024-WuGJ

If you can confidently answer these,
you’re already ahead of most candidates.

More Snowflake & dbt interview content coming soon 🚀

#Snowflake #DBT #DataEngineering #SQLInterviews #TCS #Analytics #CareerGrowth

🧠 Amazon SQL Interview Challenge
This is an interesting challenge ,please take a look

Ever tried applying Pythagoras theorem in SQL? 😄

You’re given triangle sides stored row-wise and your task is to identify which CombinationID forms a right-angled triangle.

📐 Rule to apply:
H² = P² + B² (longest side matters!)



If this showed up in an interview, how would you approach it?

https://www.linkedin.com/posts/adityabansal095_sql-amazon-amazoninterview-activity-7422150064292282368-fT9O

#SQL #SQLInterview #AmazonInterview #DataEngineering #Analytics #SQLChallenge

📊 Weekend Upskilling Idea: Build a Real Data Portfolio

If you’re stuck on what dataset to use for your next project — this list will save you hours.

Pick one dataset aligned with the industry you want to work in and build something meaningful around it 👇

🛍 Retail
Online Retail Sales (500k+ transactions)
Great for customer segmentation & sales trends
🔗 https://lnkd.in/d6H26umG

🏥 Healthcare
WHO Global Health Data (194 countries)
Perfect for time series & geo analysis
🔗 https://lnkd.in/dMfCuDqM

💰 Finance
World Bank Open Data (GDP, inflation, trade)
Ideal for economic insights & forecasting
🔗 https://data.worldbank.org

🚕 Transportation
NYC Taxi Trips (millions of rides)
Demand forecasting & pricing analysis
🔗 https://lnkd.in/deVUEmmC

🎵 Entertainment
Spotify Top Songs (audio features)
Clustering & recommendation systems
🔗 https://lnkd.in/d6u8BjxD

👥 HR & Workforce
Employee Attrition Dataset
Churn prediction & retention analysis
🔗 https://lnkd.in/dTgGKfDG

📣 Marketing
Marketing Campaign Data
Campaign ROI & customer profiling
🔗 https://lnkd.in/d_4MFM_j

🎓 Education
Student Performance Dataset
Predictive modeling & insights
🔗 https://lnkd.in/dFv24vAs

🛒 E-Commerce
Amazon Product Reviews
Sentiment analysis & rating prediction
🔗 https://lnkd.in/dZMvTDNj

🚚 Logistics
Supply Chain Dataset
Cost optimization & efficiency analysis
🔗 https://lnkd.in/d_4MFM_j

💡 Weekend reminder:
You don’t need to finish a full project in one go.
Just start — explore the data, ask questions, write a few queries.

Small effort this weekend = big confidence boost later 🚀

Save this list and pick one dataset to work on.

#dataengineer #SQL #careers #projects #learning #upskill

🎯 Data Engineering Interview in 30 Days? Here’s the Game Plan.

If I had an interview next month, this is exactly how I’d prepare 👇

🧠 Strengthen the Basics
• Revise core SQL concepts
• Solve 20–30 recent SQL questions
• Practice 20–30 Python coding problems

⚡ Spark & Big Data
• Understand PySpark fundamentals
• RDDs vs DataFrames vs Datasets
• Practice top PySpark programs

🏗 Data Engineering Foundations
• Revise Data Warehousing concepts
• Understand your project’s data model
• Review cloud services used

💻 Practical Knowledge
• Essential Linux commands
• Be ready to explain your project clearly
• Know your roles & responsibilities
• Understand implementation details

📚 Interview Readiness
• Common DE interview questions
• Read interview experiences of the target company

💡 30 days is more than enough — if you prepare with focus.

Start today. Small daily effort > last week panic 🚀

#dataengineer #jobopportunity #learning #interview #SQLInterview

When I give KT to my junior 😂😂 on running the TRUNCATE statement

Hey Engineers
Another freelance opportunity

I have a friend who needs some one who is good at SQL,SSIS,SSRS ,PostGreSQL
and Airflow

The client wants to migrate existing SSIS ETL packages


Please ping me on linkedin if you are interested.
linkedin.com/in/adityabansal095

#hiring #freelancer #jobalert #jobopportunity #ETL #SQLCommunity

Hi

Hope you're doing well.

We’re currently hiring for a Senior Python Developer role with one of our global consulting firm clients in pan India location , for a high-impact InsurTech transformation project.

Role highlights:

5+ years of experience in Python backend development

Mandatory experience in insurance products (Life / Health / General Insurance)

Strong exposure to insurance systems, APIs, and backend platforms

Opportunity to work on a large-scale InsurTech program

Unique exposure to learn and work on new-age insurance platforms that are rapidly booming in the industry

This role offers both deep insurance domain exposure and future-facing platform learning, making it a strong long-term career opportunity.

If this aligns with your profile or career direction, I’d be happy to share more details.
Also, referrals are most welcome and truly appreciated.

Warm regards,
Soham Ganguly
EliteRecruitments
www.eliterecruitments.com
https://www.linkedin.com/company/eliterecruitments

#hiring #jobalert #jobopportunity #python

Please check this job
Refer your friends if anyone is looking

🔥 Fractal Data Engineer Interview (23 LPA + 2L Variable)

This wasn’t about textbook SQL.
It was about real-world data engineering.

Here’s how it went 👇

📞 Screening
→ SQL + Python basics

💻 Round 1
→ Medium SQL problem
→ PySpark optimization
→ Kafka architecture
→ Custom PySpark function

🧠 Round 2 (Technical Deep Dive)
→ My project architecture
→ Design a scalable ETL from scratch
→ Schema evolution in Delta Lake
→ Azure stack discussion

👔 Round 3 (Managerial)
→ Leadership + ownership
→ Live coding (ETL test cases)
→ Real production challenges

💡 What they really tested:
Reliability. Scalability. Decision-making. Ownership.

Not memorized syntax.

🔥 Cracked 100 DAX Interview Questions — Here’s What Actually Matters

Power BI interviews aren’t basic anymore.

If you’re preparing for Data Analyst or BI roles, these DAX concepts are non-negotiable:

✅ SUM vs SUMX — Aggregation vs row-by-row evaluation
✅ CALCULATE — The king of filter context
✅ RANKX, FILTER, ALL, ALLEXCEPT — Core for dynamic reports
✅ Time Intelligence — TOTALYTD, SAMEPERIODLASTYEAR, DATEADD
✅ DIVIDE > / — Always handle division safely

DAX isn’t about memorizing formulas.
It’s about understanding context.

If you’re serious about cracking BI interviews, spend time mastering these this week. 🚀

Mine is cricket 🏏🥹

REPOSTING

🚨 New SQL Interview Video is LIVE! 🚨

Can you solve a real KPMG SQL interview question?

The task sounds simple…
But it tests your understanding of aggregation and logic 👀

👉 Calculate:
• Total Rides
• Won Rides
• Lost Rides

Think it’s easy? Try solving it before watching.

🎥 Watch now:
👉 https://youtu.be/tFaIBqj3jUI

After watching, tell me honestly —
Did you solve it correctly on your first attempt? 😏

More real-world SQL interview questions coming soon. Stay sharp. 🔥