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🌟Microsoft Data Engineer Interview Guide (2–3 Years Experience)
💼 Target CTC: ₹25–40 LPA
📈 Difficulty Level: Medium to Hard
💡 Interview Rounds Overview
1️⃣ Technical Screening (SQL, ETL, Data Modeling)
2️⃣ On-Site/Virtual Interviews (Coding, Azure, System Design)
3️⃣ Behavioral Round (Leadership, Ownership)
4️⃣ Final HR Discussion (CTC Negotiation)
🔑 Key Topics to Master
✅ SQL & hashtag#Data Transformation
✅ Azure Data Services (Data Factory, Synapse, Databricks)
✅ ETL Workflows & Pipeline Automation
✅ Data Modeling & Warehousing Concepts
✅ Big Data Tools & Distributed Systems
🧠 Sample Questions (Medium to Hard)
Round 1: SQL & Data Modeling
1️⃣ SQL Challenge:
Write a query to identify duplicate records in a table based on one or more columns.
📌 Expected Output: List of duplicate records with the count of occurrences for each duplicate entry.
2️⃣ Data Transformation:
Given a sales table, write a query to find the running total of sales per month for the current year.
3️⃣ Data Modeling Scenario:
• Design a dimensional model for an e-commerce business focusing on product, sales, and customer dimensions.
• How would you handle slowly changing dimensions (SCDs)?
Round 2: Azure & ETL Design
1️⃣ Azure Data Factory (ADF):
Explain how you’d build an ETL pipeline to load incremental data from an on-prem SQL database to Azure Synapse Analytics.
2️⃣ Azure Functions:
Describe how Azure Functions can be used to handle event-driven workflows in a data pipeline.
3️⃣ Error Handling in ETL Pipelines:
What mechanisms would you implement to handle failures in a multi-stage ETL pipeline?
Round 3: System Design
1️⃣ Case Study:
You are tasked with designing a real-time data ingestion pipeline for processing millions of log entries per second. What tools and architecture would you recommend?
2️⃣ Data Partitioning Strategy:
How would you implement a partitioning strategy for a 100TB dataset to ensure efficient querying and minimal latency?
3️⃣ Design Trade-Offs:
Discuss the trade-offs between using star schema vs. snowflake schema in a data warehouse.
Round 4: Behavioral Questions
1️⃣ Ownership:
Describe a situation where you had to resolve a critical data pipeline failure under tight deadlines. How did you manage it?
2️⃣ Team Collaboration:
How have you collaborated with cross-functional teams to deliver a large-scale data project?
🚀 Pro Tips for Success
💡 SQL Mastery: Practice writing efficient, optimized queries. Focus on window functions, CTEs, and joins.
💡 Cloud Expertise: Get hands-on with Azure Data Factory, Databricks, and Synapse Analytics.
💡 Scenario-Based Answers: Prepare for open-ended system design questions with real-world use cases.
💼 Target CTC: ₹25–40 LPA
📈 Difficulty Level: Medium to Hard
💡 Interview Rounds Overview
1️⃣ Technical Screening (SQL, ETL, Data Modeling)
2️⃣ On-Site/Virtual Interviews (Coding, Azure, System Design)
3️⃣ Behavioral Round (Leadership, Ownership)
4️⃣ Final HR Discussion (CTC Negotiation)
🔑 Key Topics to Master
✅ SQL & hashtag#Data Transformation
✅ Azure Data Services (Data Factory, Synapse, Databricks)
✅ ETL Workflows & Pipeline Automation
✅ Data Modeling & Warehousing Concepts
✅ Big Data Tools & Distributed Systems
🧠 Sample Questions (Medium to Hard)
Round 1: SQL & Data Modeling
1️⃣ SQL Challenge:
Write a query to identify duplicate records in a table based on one or more columns.
📌 Expected Output: List of duplicate records with the count of occurrences for each duplicate entry.
2️⃣ Data Transformation:
Given a sales table, write a query to find the running total of sales per month for the current year.
3️⃣ Data Modeling Scenario:
• Design a dimensional model for an e-commerce business focusing on product, sales, and customer dimensions.
• How would you handle slowly changing dimensions (SCDs)?
Round 2: Azure & ETL Design
1️⃣ Azure Data Factory (ADF):
Explain how you’d build an ETL pipeline to load incremental data from an on-prem SQL database to Azure Synapse Analytics.
2️⃣ Azure Functions:
Describe how Azure Functions can be used to handle event-driven workflows in a data pipeline.
3️⃣ Error Handling in ETL Pipelines:
What mechanisms would you implement to handle failures in a multi-stage ETL pipeline?
Round 3: System Design
1️⃣ Case Study:
You are tasked with designing a real-time data ingestion pipeline for processing millions of log entries per second. What tools and architecture would you recommend?
2️⃣ Data Partitioning Strategy:
How would you implement a partitioning strategy for a 100TB dataset to ensure efficient querying and minimal latency?
3️⃣ Design Trade-Offs:
Discuss the trade-offs between using star schema vs. snowflake schema in a data warehouse.
Round 4: Behavioral Questions
1️⃣ Ownership:
Describe a situation where you had to resolve a critical data pipeline failure under tight deadlines. How did you manage it?
2️⃣ Team Collaboration:
How have you collaborated with cross-functional teams to deliver a large-scale data project?
🚀 Pro Tips for Success
💡 SQL Mastery: Practice writing efficient, optimized queries. Focus on window functions, CTEs, and joins.
💡 Cloud Expertise: Get hands-on with Azure Data Factory, Databricks, and Synapse Analytics.
💡 Scenario-Based Answers: Prepare for open-ended system design questions with real-world use cases.
🌟Microsoft Data Engineer Interview Guide (2–3 Years Experience)
💼 Target CTC: ₹25–40 LPA
📈 Difficulty Level: Medium to Hard
💡 Interview Rounds Overview
1️⃣ Technical Screening (SQL, ETL, Data Modeling)
2️⃣ On-Site/Virtual Interviews (Coding, Azure, System Design)
3️⃣ Behavioral Round (Leadership, Ownership)
4️⃣ Final HR Discussion (CTC Negotiation)
🔑 Key Topics to Master
✅ SQL & hashtag#Data Transformation
✅ Azure Data Services (Data Factory, Synapse, Databricks)
✅ ETL Workflows & Pipeline Automation
✅ Data Modeling & Warehousing Concepts
✅ Big Data Tools & Distributed Systems
🧠 Sample Questions (Medium to Hard)
Round 1: SQL & Data Modeling
1️⃣ SQL Challenge:
Write a query to identify duplicate records in a table based on one or more columns.
📌 Expected Output: List of duplicate records with the count of occurrences for each duplicate entry.
2️⃣ Data Transformation:
Given a sales table, write a query to find the running total of sales per month for the current year.
3️⃣ Data Modeling Scenario:
• Design a dimensional model for an e-commerce business focusing on product, sales, and customer dimensions.
• How would you handle slowly changing dimensions (SCDs)?
Round 2: Azure & ETL Design
1️⃣ Azure Data Factory (ADF):
Explain how you’d build an ETL pipeline to load incremental data from an on-prem SQL database to Azure Synapse Analytics.
2️⃣ Azure Functions:
Describe how Azure Functions can be used to handle event-driven workflows in a data pipeline.
3️⃣ Error Handling in ETL Pipelines:
What mechanisms would you implement to handle failures in a multi-stage ETL pipeline?
Round 3: System Design
1️⃣ Case Study:
You are tasked with designing a real-time data ingestion pipeline for processing millions of log entries per second. What tools and architecture would you recommend?
2️⃣ Data Partitioning Strategy:
How would you implement a partitioning strategy for a 100TB dataset to ensure efficient querying and minimal latency?
3️⃣ Design Trade-Offs:
Discuss the trade-offs between using star schema vs. snowflake schema in a data warehouse.
Round 4: Behavioral Questions
1️⃣ Ownership:
Describe a situation where you had to resolve a critical data pipeline failure under tight deadlines. How did you manage it?
2️⃣ Team Collaboration:
How have you collaborated with cross-functional teams to deliver a large-scale data project?
🚀 Pro Tips for Success
💡 SQL Mastery: Practice writing efficient, optimized queries. Focus on window functions, CTEs, and joins.
💡 Cloud Expertise: Get hands-on with Azure Data Factory, Databricks, and Synapse Analytics.
💡 Scenario-Based Answers: Prepare for open-ended system design questions with real-world use cases.
💼 Target CTC: ₹25–40 LPA
📈 Difficulty Level: Medium to Hard
💡 Interview Rounds Overview
1️⃣ Technical Screening (SQL, ETL, Data Modeling)
2️⃣ On-Site/Virtual Interviews (Coding, Azure, System Design)
3️⃣ Behavioral Round (Leadership, Ownership)
4️⃣ Final HR Discussion (CTC Negotiation)
🔑 Key Topics to Master
✅ SQL & hashtag#Data Transformation
✅ Azure Data Services (Data Factory, Synapse, Databricks)
✅ ETL Workflows & Pipeline Automation
✅ Data Modeling & Warehousing Concepts
✅ Big Data Tools & Distributed Systems
🧠 Sample Questions (Medium to Hard)
Round 1: SQL & Data Modeling
1️⃣ SQL Challenge:
Write a query to identify duplicate records in a table based on one or more columns.
📌 Expected Output: List of duplicate records with the count of occurrences for each duplicate entry.
2️⃣ Data Transformation:
Given a sales table, write a query to find the running total of sales per month for the current year.
3️⃣ Data Modeling Scenario:
• Design a dimensional model for an e-commerce business focusing on product, sales, and customer dimensions.
• How would you handle slowly changing dimensions (SCDs)?
Round 2: Azure & ETL Design
1️⃣ Azure Data Factory (ADF):
Explain how you’d build an ETL pipeline to load incremental data from an on-prem SQL database to Azure Synapse Analytics.
2️⃣ Azure Functions:
Describe how Azure Functions can be used to handle event-driven workflows in a data pipeline.
3️⃣ Error Handling in ETL Pipelines:
What mechanisms would you implement to handle failures in a multi-stage ETL pipeline?
Round 3: System Design
1️⃣ Case Study:
You are tasked with designing a real-time data ingestion pipeline for processing millions of log entries per second. What tools and architecture would you recommend?
2️⃣ Data Partitioning Strategy:
How would you implement a partitioning strategy for a 100TB dataset to ensure efficient querying and minimal latency?
3️⃣ Design Trade-Offs:
Discuss the trade-offs between using star schema vs. snowflake schema in a data warehouse.
Round 4: Behavioral Questions
1️⃣ Ownership:
Describe a situation where you had to resolve a critical data pipeline failure under tight deadlines. How did you manage it?
2️⃣ Team Collaboration:
How have you collaborated with cross-functional teams to deliver a large-scale data project?
🚀 Pro Tips for Success
💡 SQL Mastery: Practice writing efficient, optimized queries. Focus on window functions, CTEs, and joins.
💡 Cloud Expertise: Get hands-on with Azure Data Factory, Databricks, and Synapse Analytics.
💡 Scenario-Based Answers: Prepare for open-ended system design questions with real-world use cases.
Most asked SQL Interview Questions
1. Explain order of execution of SQL.
2. What is difference between where and having?
3. What is the use of group by?
4. Explain all types of joins in SQL?
5. What are triggers in SQL?
6. What is stored procedure in SQL
7. Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8. What is the difference between DROP vs DELETE vs TRUNCATE?
9. What is difference between DML, DDL and DCL?
10. Which is faster between CTE and Subquery?
11. What are constraints and types of Constraints?
12. What is normalization?
13. Difference between Group By and Where Clause?
14. Explain View concepts ?
15. What are different types of constraints?
16. Difference between char and Varchar?
17. What is an index? Explain its different types.
18. Write an SQL query to find the names of employees starting with ‘A’.
19. How many types of clauses in SQL?
26. Difference between UNION and UNION ALL in SQL?
27. What are the various types of relationships in SQL?
28. Difference between Primary Key and Foreign Key?
29. What is the difference between where and having?
30. Find the second highest salary of an employee?
31. Difference between Function and Store procedure ?
32. How would you optimize a slow SQL query?
33. Difference between INNER JOIN and OUTER JOIN?
34. How do you handle duplicate rows in a SQL query?
35. Write a SQL query to find the top 3 departments with the highest average salary.
36. Write a SQL query to find the employees who have the same name and work in the same department.
37. Write a SQL query to find the departments with no employees.
38. How do you use indexing to improve SQL query performance?
39. Write a SQL query to find the employees who have worked for more than 5 years.
40. What is the difference between SUBQUERY and JOIN?
41. Write a SQL query to find the top 2 products with the highest sales.
42. How do you use stored procedures to improve SQL query performance?
43. Write a SQL query to find the customers who have placed an order but have not made a payment.
44. Write a SQL query to find the employees who work in the same department as their manager.
45. How do you use window functions to solve complex queries?
46. Write a SQL query to find the top 3 products with the highest average price.
47. Write a SQL query to find the employees who have not taken any leave in the last 6 months.
48. Write down various types of relationships in SQL?
49. What is the difference between Cluster and Non-Cluster Index?
50. Why do we use Commit and Rollback commands?
51. What are indexes in SQL?
52. What are aggregate functions? Can you name a few?
1. Explain order of execution of SQL.
2. What is difference between where and having?
3. What is the use of group by?
4. Explain all types of joins in SQL?
5. What are triggers in SQL?
6. What is stored procedure in SQL
7. Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8. What is the difference between DROP vs DELETE vs TRUNCATE?
9. What is difference between DML, DDL and DCL?
10. Which is faster between CTE and Subquery?
11. What are constraints and types of Constraints?
12. What is normalization?
13. Difference between Group By and Where Clause?
14. Explain View concepts ?
15. What are different types of constraints?
16. Difference between char and Varchar?
17. What is an index? Explain its different types.
18. Write an SQL query to find the names of employees starting with ‘A’.
19. How many types of clauses in SQL?
26. Difference between UNION and UNION ALL in SQL?
27. What are the various types of relationships in SQL?
28. Difference between Primary Key and Foreign Key?
29. What is the difference between where and having?
30. Find the second highest salary of an employee?
31. Difference between Function and Store procedure ?
32. How would you optimize a slow SQL query?
33. Difference between INNER JOIN and OUTER JOIN?
34. How do you handle duplicate rows in a SQL query?
35. Write a SQL query to find the top 3 departments with the highest average salary.
36. Write a SQL query to find the employees who have the same name and work in the same department.
37. Write a SQL query to find the departments with no employees.
38. How do you use indexing to improve SQL query performance?
39. Write a SQL query to find the employees who have worked for more than 5 years.
40. What is the difference between SUBQUERY and JOIN?
41. Write a SQL query to find the top 2 products with the highest sales.
42. How do you use stored procedures to improve SQL query performance?
43. Write a SQL query to find the customers who have placed an order but have not made a payment.
44. Write a SQL query to find the employees who work in the same department as their manager.
45. How do you use window functions to solve complex queries?
46. Write a SQL query to find the top 3 products with the highest average price.
47. Write a SQL query to find the employees who have not taken any leave in the last 6 months.
48. Write down various types of relationships in SQL?
49. What is the difference between Cluster and Non-Cluster Index?
50. Why do we use Commit and Rollback commands?
51. What are indexes in SQL?
52. What are aggregate functions? Can you name a few?
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