🧠 This complex SQL question from Google looked simple… until I actually started solving it.
Let’s just say — a plain
I used a mix of aggregates + window functions to crack it — and the approach might surprise you.
🎥 https://youtu.be/Qvudg-uYwk0?si=IQnB_HofAvXg21oy
#SQL #InterviewPrep #SQLInterview #DataEngineering
Let’s just say — a plain
JOIN wasn’t enough. 😉I used a mix of aggregates + window functions to crack it — and the approach might surprise you.
🎥 https://youtu.be/Qvudg-uYwk0?si=IQnB_HofAvXg21oy
#SQL #InterviewPrep #SQLInterview #DataEngineering
YouTube
SQL Server Complex Interview Question | Find number of flags for videos reviewed by Youtube
🚀 SQL Interview Question | Google SQL Challenge | Window Functions Explained
In this video, I solve a real SQL interview question asked in Google from the StrataScratch platform.
We’ll walk through the problem step-by-step, understand the requirements, and…
In this video, I solve a real SQL interview question asked in Google from the StrataScratch platform.
We’ll walk through the problem step-by-step, understand the requirements, and…
SQL Junction
Senior Data Engineer (Snowflake +DBT +Airflow).docx
#JobAlert #JobOpening
One of my friends in looking for Snowflake Dbt Airflow Data Engineer for Pune and Ahmedabad location
I have put the JD ,if you are looking to switch
Do reach out to me on linkedin
linkedin.com/in/adityabansal095
#DataEngineering #DataEngineerJob
#SQL #CareerOpportunity
One of my friends in looking for Snowflake Dbt Airflow Data Engineer for Pune and Ahmedabad location
I have put the JD ,if you are looking to switch
Do reach out to me on linkedin
linkedin.com/in/adityabansal095
#DataEngineering #DataEngineerJob
#SQL #CareerOpportunity
I am hiring you as a Snowflake data engineer in 2025, if you know all these concepts.
From ingestion 📥 to transformation 🔄 to delivery 📊 — everything just flows seamlessly.
If you’re looking to learn Snowflake step by step, here’s a great Coursera course I recommend.
imp.i384100.net/snowflake_data
#SQL #Snowflake #DataEngineering #ETL
From ingestion 📥 to transformation 🔄 to delivery 📊 — everything just flows seamlessly.
If you’re looking to learn Snowflake step by step, here’s a great Coursera course I recommend.
imp.i384100.net/snowflake_data
#SQL #Snowflake #DataEngineering #ETL
😲 99% of SQL learners struggle with this problem!
You get a
MM, CI, CO (0.5 pts each) CD, CL, CM (1 pt each)
💥 Challenge: Calculate the total points scored by each club using SQL. Sounds simple? Wait till you try it. 😏
Most people miss the key logic 👀
Can you crack it before watching the solution?
🎥 Full breakdown + solution:
👉 SQL Challenge: Calculate Total Club Points | SQL Interview Question Explained
https://youtu.be/V-mMZ4hhhQE
#SQL #SQLChallenge #DataEngineering #SQLInterview #LearnSQL
You get a
Club table where each member earns rewards like:MM, CI, CO (0.5 pts each) CD, CL, CM (1 pt each)
💥 Challenge: Calculate the total points scored by each club using SQL. Sounds simple? Wait till you try it. 😏
Most people miss the key logic 👀
Can you crack it before watching the solution?
🎥 Full breakdown + solution:
👉 SQL Challenge: Calculate Total Club Points | SQL Interview Question Explained
https://youtu.be/V-mMZ4hhhQE
#SQL #SQLChallenge #DataEngineering #SQLInterview #LearnSQL
🚀 Level up your SQL game!
I’ve created a YouTube playlist where I break down real SQL interview questions just like top companies ask.
Check it out here 👇 👉 https://youtube.com/playlist?list=PLU1HobJd_JCqjcZwUCc6s8avJutoIjyIF&si=pcJTwrke6No-SVyl
Let’s crack SQL interviews together! 🔥 #SQL #SQLInterviews #DataEngineering #LearnSQL
I’ve created a YouTube playlist where I break down real SQL interview questions just like top companies ask.
From tricky joins to logic-based challenges… everything is covered in simple, clear explanations 🎯Whether you’re preparing for interviews or just sharpening your skills, this playlist will help you upgrade fast 💡
Check it out here 👇 👉 https://youtube.com/playlist?list=PLU1HobJd_JCqjcZwUCc6s8avJutoIjyIF&si=pcJTwrke6No-SVyl
Let’s crack SQL interviews together! 🔥 #SQL #SQLInterviews #DataEngineering #LearnSQL
🚀 New SQL Hard Challenge is LIVE!
Today’s problem looks simple… until you try it 😅
You’re given a table of products and categories — and your task is to swap records inside each category using SQL window functions.
Most people get stuck on the logic 👀
Can YOU figure out the right approach before watching the solution?
🎥 Watch the full video here:
👉 DELOITTE HARD SQL Interview Question in Hindi | Swap records Inversely
https://youtu.be/jOrTXXleDcg
If you’re preparing for SQL interviews or just love brain-teasing SQL problems, this challenge is for you 🔥
#SQL #SQLChallenge #DataEngineering #SQLInterview #PracticeSQL
Today’s problem looks simple… until you try it 😅
You’re given a table of products and categories — and your task is to swap records inside each category using SQL window functions.
Most people get stuck on the logic 👀
Can YOU figure out the right approach before watching the solution?
🎥 Watch the full video here:
👉 DELOITTE HARD SQL Interview Question in Hindi | Swap records Inversely
https://youtu.be/jOrTXXleDcg
If you’re preparing for SQL interviews or just love brain-teasing SQL problems, this challenge is for you 🔥
#SQL #SQLChallenge #DataEngineering #SQLInterview #PracticeSQL
YouTube
DELOITTE HARD SQL Interview Question in Hindi | Swap records Inversely
In this video, we solve a very interesting SQL problem involving window functions and an update operation.
You’re given a Products table with ProductID, Product, and Category.
The task is to swap the ProductIDs of the products within each category using SQL!…
You’re given a Products table with ProductID, Product, and Category.
The task is to swap the ProductIDs of the products within each category using SQL!…
🔥1
🎯 New SQL Interview Question on YouTube!
A real Deloitte Interview Question that tests: • Window functions • Logical thinking under pressure • Your ability to connect dates correctly 📅⚙️
DELOITTE HARD SQL Interview Question in Hindi | Find Start and End Dates for Consecutive rows
https://youtu.be/ZPcV0OmSaIo
Most candidates struggle here… Can YOU solve it? 🤔
Watch now 👇
🔥
#SQL #InterviewPrep #DataEngineering #LearnSQL #SQLServer #Programming #SQLPractice #TechInterview #YouTubeChannel #SQLCommunity #SQLJunction #AdityaBansal
A real Deloitte Interview Question that tests: • Window functions • Logical thinking under pressure • Your ability to connect dates correctly 📅⚙️
DELOITTE HARD SQL Interview Question in Hindi | Find Start and End Dates for Consecutive rows
https://youtu.be/ZPcV0OmSaIo
Most candidates struggle here… Can YOU solve it? 🤔
Watch now 👇
🔥
#SQL #InterviewPrep #DataEngineering #LearnSQL #SQLServer #Programming #SQLPractice #TechInterview #YouTubeChannel #SQLCommunity #SQLJunction #AdityaBansal
YouTube
DELOITTE HARD SQL Interview Question in Hindi | Find Start and End Dates for Consecutive rows
🎯 SQL Interview Challenge – Can You Solve This?
In this video, we take a real-world problem involving event logs and use SQL window functions (ROW_NUMBER) to group consecutive records by date. This is a popular interview question used in top tech and data…
In this video, we take a real-world problem involving event logs and use SQL window functions (ROW_NUMBER) to group consecutive records by date. This is a popular interview question used in top tech and data…
FAANG SQL Challenge: Can you solve "The Delimiter Trap"? 🧩
I just dropped a new breakdown of a classic interview problem that trips up even Senior Data Engineers.
The Task: Extract and calculate reward points from a single "messy" column (e.g., `'MM:CI:CD'`).
Why you should watch:
✅ Learn the cleanest way to use
✅ Master Conditional Aggregation (no more spaghetti code!).
✅ Avoid the #1 over-engineering mistake candidates make in FAANG interviews.
Stop struggling with messy data—master the logic in 5 minutes.
Watch the full solution here:
👇👇👇
https://youtu.be/Pg5F8_ViXE8
Which one is faster for this—`STRING_SPLIT` or
#SQL #InterviewPrep #DataEngineering #SQLJunction #SQLInterview
I just dropped a new breakdown of a classic interview problem that trips up even Senior Data Engineers.
The Task: Extract and calculate reward points from a single "messy" column (e.g., `'MM:CI:CD'`).
Why you should watch:
✅ Learn the cleanest way to use
STRING_SPLIT.✅ Master Conditional Aggregation (no more spaghetti code!).
✅ Avoid the #1 over-engineering mistake candidates make in FAANG interviews.
Stop struggling with messy data—master the logic in 5 minutes.
Watch the full solution here:
👇👇👇
https://youtu.be/Pg5F8_ViXE8
Which one is faster for this—`STRING_SPLIT` or
CROSS APPLY? Let me know in the YouTube comments! 🚀#SQL #InterviewPrep #DataEngineering #SQLJunction #SQLInterview
YouTube
FAANG SQL Interview Challenge | Calculate Total Club Points
🎯 SQL Challenge – Can You Solve This?
In this video, we’ll solve a real SQL interview-style problem involving reward points and club memberships.
Table Create Statements:
Create Table Club (
Club_Id int,
Member_Id int,
EDU varchar(30))
Insert into Club…
In this video, we’ll solve a real SQL interview-style problem involving reward points and club memberships.
Table Create Statements:
Create Table Club (
Club_Id int,
Member_Id int,
EDU varchar(30))
Insert into Club…
👍1
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
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
❤1
🧠 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
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
🚀 Essential SQL Commands Every Data Professional Should Know
Whether you’re preparing for SQL interviews or working with databases daily, these commands form the backbone of SQL.
Here’s a quick refresher 👇
🔹 SELECT – Retrieve data from a table
🔹 INSERT – Add new records into a table
🔹 UPDATE – Modify existing data
🔹 DELETE – Remove specific records
📦 Database Structure
🔹 CREATE – Create new database objects (tables, databases)
🔹 ALTER – Modify the structure of an existing object
🔹 DROP – Delete an entire table or database
📊 Filtering & Analysis
🔹 WHERE – Filter records based on conditions
🔹 GROUP BY – Group rows with similar values
🔹 HAVING – Filter aggregated results
🔗 Working with Multiple Tables
🔹 JOIN – Combine data from multiple tables
⚡ Performance
🔹 INDEX – Speeds up data retrieval in large tables
📌 Tip:
Mastering these fundamentals makes solving complex SQL problems much easier.
🔥 Try this today:
Pick one command and write a small query to practice it.
#SQL #LearnSQL #DataEngineering #DataAnalytics
Whether you’re preparing for SQL interviews or working with databases daily, these commands form the backbone of SQL.
Here’s a quick refresher 👇
🔹 SELECT – Retrieve data from a table
🔹 INSERT – Add new records into a table
🔹 UPDATE – Modify existing data
🔹 DELETE – Remove specific records
📦 Database Structure
🔹 CREATE – Create new database objects (tables, databases)
🔹 ALTER – Modify the structure of an existing object
🔹 DROP – Delete an entire table or database
📊 Filtering & Analysis
🔹 WHERE – Filter records based on conditions
🔹 GROUP BY – Group rows with similar values
🔹 HAVING – Filter aggregated results
🔗 Working with Multiple Tables
🔹 JOIN – Combine data from multiple tables
⚡ Performance
🔹 INDEX – Speeds up data retrieval in large tables
📌 Tip:
Mastering these fundamentals makes solving complex SQL problems much easier.
🔥 Try this today:
Pick one command and write a small query to practice it.
#SQL #LearnSQL #DataEngineering #DataAnalytics
❤1👍1
🚨 Quick SQL Reality Check
Most developers think:
COUNT(*) = COUNT(Column)
But that’s not always true 👀
A single NULL value can completely change the result.
I recorded a quick 30-second Short explaining the difference with a simple example.
🎥 Watch here:
👉 [Paste YouTube Shorts Link]
Trust me, this is one concept worth remembering for SQL interviews and real-world projects.
Or, if you want something more aggressive:
⚠️ SQL Interview Trap
What will these return?
COUNT(*)
COUNT(Salary)
Same answer? 🤔
Most people get this wrong because of NULL values.
I explained it in a quick YouTube Short👇
🎥 Watch Now:
👉
https://youtube.com/shorts/1rHHZmMHx6E?feature=share
Did you know the answer before watching? 😏
Most developers think:
COUNT(*) = COUNT(Column)
But that’s not always true 👀
A single NULL value can completely change the result.
I recorded a quick 30-second Short explaining the difference with a simple example.
🎥 Watch here:
👉 [Paste YouTube Shorts Link]
Trust me, this is one concept worth remembering for SQL interviews and real-world projects.
Or, if you want something more aggressive:
⚠️ SQL Interview Trap
What will these return?
COUNT(*)
COUNT(Salary)
Same answer? 🤔
Most people get this wrong because of NULL values.
I explained it in a quick YouTube Short👇
🎥 Watch Now:
👉
https://youtube.com/shorts/1rHHZmMHx6E?feature=share
Did you know the answer before watching? 😏
❤1
🔥 New YouTube Video Alert
Can You Solve This Deloitte SQL Interview Question?
You’re given a products table where the category is available only for the first product, while the following rows contain NULL.
🎯 Challenge:
How would you fill those NULL category values with the correct category?
💡 Hint: Think about Window Functions 👀
This is a great SQL problem to test your understanding of NULL handling + data transformation.
👇 What would you use?
🅰️ LAG()
🅱️ LEAD()
🅲️ LAST_VALUE()
🅳️ ROW_NUMBER()
🎬 Solution video
Fill Missing Categories in SQL | Hard Deloitte Interview Question
https://youtu.be/IX9NBK3Yx-M
🚀
Check it out now and let me know in comments ,What did you learn?
#SQL #SQLInterview #Deloitte #SQLChallenge #DataEngineering #Snowflake
Can You Solve This Deloitte SQL Interview Question?
You’re given a products table where the category is available only for the first product, while the following rows contain NULL.
Beverages → Coca ColaNULL → PepsiNULL → SpriteNULL → FantaSnacks → LaysNULL → DoritosNULL → Kurkure🎯 Challenge:
How would you fill those NULL category values with the correct category?
💡 Hint: Think about Window Functions 👀
This is a great SQL problem to test your understanding of NULL handling + data transformation.
👇 What would you use?
🅰️ LAG()
🅱️ LEAD()
🅲️ LAST_VALUE()
🅳️ ROW_NUMBER()
🎬 Solution video
Fill Missing Categories in SQL | Hard Deloitte Interview Question
https://youtu.be/IX9NBK3Yx-M
🚀
Check it out now and let me know in comments ,What did you learn?
#SQL #SQLInterview #Deloitte #SQLChallenge #DataEngineering #Snowflake
YouTube
Fill Missing Categories in SQL | Hard Deloitte Interview Question
In this SQL interview question, we have a product table where the category is available for the first product but appears as NULL for the following products.
🎯 The challenge:
Fill the missing category values by carrying forward the last non-NULL category…
🎯 The challenge:
Fill the missing category values by carrying forward the last non-NULL category…
👍1
🚀 Azure and ETL data engineering roles worth exploring
If you are working with SQL, Spark, Airflow, Databricks, or cloud pipelines, these roles align well with practical data engineering workflows.
💼 Role: Azure Data Engineer
🏢 Company: Tata Consultancy Services
📍 Location: Bengaluru
🌎 Work mode: onsite
✨ Why it is worth checking: Strong Azure stack with ADF, Databricks, Synapse, PySpark, ETL/ELT, and data warehousing exposure.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-tata-consultancy-bengaluru-abb0b3eb
💼 Role: Senior Data Engineer
🏢 Company: Satwic
📍 Location: India
🌎 Work mode: remote
✨ Why it is worth checking: Good fit for engineers working on Azure migrations, Synapse, Databricks, Spark, and large-scale data pipelines.
🔗 https://artha.link/@adityabansal095/jobs/senior-data-engineer-satwic-inc-india-8610633d
💼 Role: Data Engineer
🏢 Company: TIGI HR
📍 Location: Gurugram
🌎 Work mode: remote
✨ Why it is worth checking: Covers Airflow, ADF, SQL, Python, ETL workflows, and data warehouse projects.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-tigi-hr-gurugram-e0612e8f
Share with someone preparing for their next data engineering move.
#DataEngineering #AzureDataEngineer #SQL #Databricks #ETL #Airflow #CloudDataEngineering
If you are working with SQL, Spark, Airflow, Databricks, or cloud pipelines, these roles align well with practical data engineering workflows.
💼 Role: Azure Data Engineer
🏢 Company: Tata Consultancy Services
📍 Location: Bengaluru
🌎 Work mode: onsite
✨ Why it is worth checking: Strong Azure stack with ADF, Databricks, Synapse, PySpark, ETL/ELT, and data warehousing exposure.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-tata-consultancy-bengaluru-abb0b3eb
💼 Role: Senior Data Engineer
🏢 Company: Satwic
📍 Location: India
🌎 Work mode: remote
✨ Why it is worth checking: Good fit for engineers working on Azure migrations, Synapse, Databricks, Spark, and large-scale data pipelines.
🔗 https://artha.link/@adityabansal095/jobs/senior-data-engineer-satwic-inc-india-8610633d
💼 Role: Data Engineer
🏢 Company: TIGI HR
📍 Location: Gurugram
🌎 Work mode: remote
✨ Why it is worth checking: Covers Airflow, ADF, SQL, Python, ETL workflows, and data warehouse projects.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-tigi-hr-gurugram-e0612e8f
Share with someone preparing for their next data engineering move.
#DataEngineering #AzureDataEngineer #SQL #Databricks #ETL #Airflow #CloudDataEngineering
❤4
🚀 Data engineering roles worth checking for SQL learners
💼 Role: Data Engineer
🏢 Company: EXL
📍 Location: India, IN
🌎 Work mode: remote
✨ Why it is worth checking: Strong exposure to AWS Glue, Redshift, Athena, PySpark, ETL/ELT pipelines, and data warehousing concepts.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-exl-india-ab6b2cd2
💼 Role: Data Engineer
🏢 Company: Newtap Finance
📍 Location: Bengaluru, Karnataka, IN
🌎 Work mode: onsite
✨ Why it is worth checking: Hands-on work with Airflow, EMR, Spark, Athena, CDC ingestion, and lakehouse architecture.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-newtap-finance-bengaluru-36d7cd70
💼 Role: Data Engineer – Analytics & Aws
🏢 Company: Health Catalyst
📍 Location: Hyderabad, Telangana, IN
🌎 Work mode: remote
✨ Why it is worth checking: Good mix of data engineering and analytics using AWS Glue, Snowflake, SQL, Python, Kafka, and Airflow.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-analytics-aws-health-catalyst-hyderabad-14f9084d
Save this for later or share with someone preparing for data engineering interviews.
#DataEngineering #SQL #AWS #Snowflake #Airflow #ETL #Python #Jobs #JobAlert
💼 Role: Data Engineer
🏢 Company: EXL
📍 Location: India, IN
🌎 Work mode: remote
✨ Why it is worth checking: Strong exposure to AWS Glue, Redshift, Athena, PySpark, ETL/ELT pipelines, and data warehousing concepts.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-exl-india-ab6b2cd2
💼 Role: Data Engineer
🏢 Company: Newtap Finance
📍 Location: Bengaluru, Karnataka, IN
🌎 Work mode: onsite
✨ Why it is worth checking: Hands-on work with Airflow, EMR, Spark, Athena, CDC ingestion, and lakehouse architecture.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-newtap-finance-bengaluru-36d7cd70
💼 Role: Data Engineer – Analytics & Aws
🏢 Company: Health Catalyst
📍 Location: Hyderabad, Telangana, IN
🌎 Work mode: remote
✨ Why it is worth checking: Good mix of data engineering and analytics using AWS Glue, Snowflake, SQL, Python, Kafka, and Airflow.
🔗 https://artha.link/@adityabansal095/jobs/data-engineer-analytics-aws-health-catalyst-hyderabad-14f9084d
Save this for later or share with someone preparing for data engineering interviews.
#DataEngineering #SQL #AWS #Snowflake #Airflow #ETL #Python #Jobs #JobAlert
👍1
🚀 Data engineering roles with strong cloud stack exposure
If you are working on SQL, ETL pipelines, Databricks, Snowflake, or PySpark projects, these roles are worth checking.
💼 Role: Aws Data Engineer
🏢 Company: Tata Consultancy Services
📍 Location: Bengaluru, Noida, Gandhi Nagar, Pune, Chennai
✨ Why it is worth checking: Strong focus on Databricks on AWS, Delta Lake, Structured Streaming, CDC, and Medallion Architecture.
🔗 https://artha.link/@adityabansal095/jobs/aws-data-engineer-tata-consultancy-gandhinagar-92feef28
💼 Role: Azure Data Engineer
🏢 Company: Recro
📍 Location: Hyderabad, Bangalore, Pune
🌎 Work mode: hybrid
✨ Why it is worth checking: Good match if you are building Azure data pipelines with ADF, SQL, Python, PySpark, and Databricks.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-recro-pune-district-75c72d64
💼 Role: Azure Data Engineer
🏢 Company: EXL
📍 Location: Noida, Gurgaon, Pune, Bangalore, Hyderabad, Chennai
🌎 Work mode: remote
✨ Why it is worth checking: Useful for engineers working with ADF, DBT, Snowflake, and ETL/ELT workflows.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-exl-noida-6c18eb62
Save this for later or send it to someone job hunting.
#DataEngineering #SQL #Databricks #Snowflake #AzureDataFactory #PySpark #ETL
If you are working on SQL, ETL pipelines, Databricks, Snowflake, or PySpark projects, these roles are worth checking.
💼 Role: Aws Data Engineer
🏢 Company: Tata Consultancy Services
📍 Location: Bengaluru, Noida, Gandhi Nagar, Pune, Chennai
✨ Why it is worth checking: Strong focus on Databricks on AWS, Delta Lake, Structured Streaming, CDC, and Medallion Architecture.
🔗 https://artha.link/@adityabansal095/jobs/aws-data-engineer-tata-consultancy-gandhinagar-92feef28
💼 Role: Azure Data Engineer
🏢 Company: Recro
📍 Location: Hyderabad, Bangalore, Pune
🌎 Work mode: hybrid
✨ Why it is worth checking: Good match if you are building Azure data pipelines with ADF, SQL, Python, PySpark, and Databricks.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-recro-pune-district-75c72d64
💼 Role: Azure Data Engineer
🏢 Company: EXL
📍 Location: Noida, Gurgaon, Pune, Bangalore, Hyderabad, Chennai
🌎 Work mode: remote
✨ Why it is worth checking: Useful for engineers working with ADF, DBT, Snowflake, and ETL/ELT workflows.
🔗 https://artha.link/@adityabansal095/jobs/azure-data-engineer-exl-noida-6c18eb62
Save this for later or send it to someone job hunting.
#DataEngineering #SQL #Databricks #Snowflake #AzureDataFactory #PySpark #ETL
📊 Data engineering and BI roles worth exploring
If you are building SQL, ETL, analytics, or AI engineering skills, these opportunities align well with real-world data workflows and production systems.
💼 Role: Lead Ai Engineer (agentic Systems)
🏢 Company: S&P Global
📍 Location: Haryana, Gurugram, IN
✨ Why it is worth checking: Strong mix of Python, ETL, Databricks, Snowflake, Kubernetes, LangGraph, and production-grade AI systems.
🔗 https://artha.link/@adityabansal095/jobs/lead-ai-engineer-agentic-systems-s-p-global-haryana-402f311a
💼 Role: Data Analyst / Engineer
🏢 Company: Kyndryl
📍 Location: Karnataka, Bangalore, IN
✨ Why it is worth checking: Good fit if you work with SQL, Python, Snowflake, ETL/ELT, ODI, Power BI, and enterprise data warehousing.
🔗 https://artha.link/@adityabansal095/jobs/data-analyst-engineer-kyndryl-karnataka-42df3c00
💼 Role: Business Intelligence Engineer, Aop - Row Apex
🏢 Company: ASSPL - Karnataka
📍 Location: Hyderabad, Telangana, IN
✨ Why it is worth checking: Covers BI reporting, SQL, Python, ETL pipelines, Tableau/Quicksight, and analytics frameworks at scale.
🔗 https://artha.link/@adityabansal095/jobs/business-intelligence-engineer-aop-row-asspl-karnataka-hyderabad-28f3112f
Save this for later or share with someone preparing for data engineering interviews.
#DataEngineering #SQL #ETL #BusinessIntelligence #Snowflake #Python #Analytics
If you are building SQL, ETL, analytics, or AI engineering skills, these opportunities align well with real-world data workflows and production systems.
💼 Role: Lead Ai Engineer (agentic Systems)
🏢 Company: S&P Global
📍 Location: Haryana, Gurugram, IN
✨ Why it is worth checking: Strong mix of Python, ETL, Databricks, Snowflake, Kubernetes, LangGraph, and production-grade AI systems.
🔗 https://artha.link/@adityabansal095/jobs/lead-ai-engineer-agentic-systems-s-p-global-haryana-402f311a
💼 Role: Data Analyst / Engineer
🏢 Company: Kyndryl
📍 Location: Karnataka, Bangalore, IN
✨ Why it is worth checking: Good fit if you work with SQL, Python, Snowflake, ETL/ELT, ODI, Power BI, and enterprise data warehousing.
🔗 https://artha.link/@adityabansal095/jobs/data-analyst-engineer-kyndryl-karnataka-42df3c00
💼 Role: Business Intelligence Engineer, Aop - Row Apex
🏢 Company: ASSPL - Karnataka
📍 Location: Hyderabad, Telangana, IN
✨ Why it is worth checking: Covers BI reporting, SQL, Python, ETL pipelines, Tableau/Quicksight, and analytics frameworks at scale.
🔗 https://artha.link/@adityabansal095/jobs/business-intelligence-engineer-aop-row-asspl-karnataka-hyderabad-28f3112f
Save this for later or share with someone preparing for data engineering interviews.
#DataEngineering #SQL #ETL #BusinessIntelligence #Snowflake #Python #Analytics