![\"Data](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/03\/Data-Engineering-Interview-Questions-and-Answers_-Fresher-Level-1200x630.webp\" "\\"\\"")
<\/figure>\n\n\n\nIf you’re just starting your career in data engineering, employers will primarily assess your understanding of foundational concepts \u2014 databases, SQL, ETL workflows, and basic architecture. This section covers beginner-friendly questions that test your grasp on core principles and your ability to apply them in real-world scenarios.<\/p>\n\n\n\n
1. What is Data Engineering? How is it different from Data Science?<\/strong><\/h3>\n\n\n\n![\"What](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/03\/What-is-Data-Engineering_-How-is-it-different-from-Data-Science-1200x630.webp\" "\\"\\"")
<\/figure>\n\n\n\nData engineering is the discipline of designing, building, and maintaining systems and infrastructure that enable the collection, storage, and processing of large volumes of data efficiently.<\/p>\n\n\n\n
While data science<\/a> is focused on extracting insights from data using statistical methods and machine learning, data engineering is about ensuring that the data is clean, reliable, and accessible for such analysis.<\/p>\n\n\n\n2. What is a Data Pipeline?<\/strong><\/h3>\n\n\n\nA data pipeline is a set of processes that move data from one system to another \u2014 typically from a data source (like an API or database) to a storage or analytics system.<\/p>\n\n\n\n
It usually involves:<\/p>\n\n\n\n
\n- Extracting<\/strong> data from a source.<\/li>\n\n\n\n
- Transforming<\/strong> it into a usable format.<\/li>\n\n\n\n
- Loading<\/strong> it into a storage system or database.<\/li>\n<\/ul>\n\n\n\n
3. Explain the ETL process.<\/strong><\/h3>\n\n\n\n![\"ETL](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/03\/Explain-the-ETL-process-1200x630.webp\" "\\"\\"")
<\/figure>\n\n\n\nETL stands for Extract, Transform, Load<\/strong> \u2014 a traditional process used to prepare data for analysis.<\/p>\n\n\n\n\n- Extract<\/strong>: Pull data from various sources (APIs, databases, flat files).<\/li>\n\n\n\n
- Transform<\/strong>: Clean and process the data (e.g., remove nulls, convert formats, aggregate).<\/li>\n\n\n\n
- Load<\/strong>: Insert the transformed data into a target system like a data warehouse.<\/li>\n<\/ul>\n\n\n\n
4. What is the difference between OLTP and OLAP systems?<\/strong><\/h3>\n\n\n\n\n- OLTP (Online Transaction Processing):<\/strong>
<\/strong>\n\n- Used for handling high volumes of small, quick transactions.<\/li>\n\n\n\n
- Examples: Banking systems, and order entry apps.<\/li>\n\n\n\n
- Prioritizes speed and accuracy.
<\/li>\n<\/ul>\n<\/li>\n\n\n\n - OLAP (Online Analytical Processing):<\/strong>
<\/strong>\n\n- Used for complex queries on large datasets.<\/li>\n\n\n\n
- Supports reporting and analytics.<\/li>\n\n\n\n
- Example: BI dashboards, financial forecasting.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
5. What are the different types of databases used in data engineering?<\/strong><\/h3>\n\n\n\nHere are the main types:<\/p>\n\n\n\n
\n- Relational Databases (SQL)<\/strong>: Structured schema, uses tables (e.g., MySQL, PostgreSQL).
<\/li>\n\n\n\n- NoSQL Databases<\/strong><\/a>: Schema-less or flexible schemas.
\n\n- Document-based<\/em>: MongoDB<\/li>\n\n\n\n
- Key-value stores<\/em>: Redis<\/li>\n\n\n\n
- Columnar stores<\/em>: Cassandra
<\/li>\n<\/ul>\n<\/li>\n\n\n\n- Columnar Databases<\/strong>: Optimized for analytics (e.g., Amazon Redshift, Google BigQuery).
<\/li>\n\n\n\n- Time-Series Databases<\/strong>: Used for time-stamped data (e.g., InfluxDB, TimescaleDB).<\/li>\n<\/ul>\n\n\n\n
Each is suited for specific use cases based on performance, scalability, and structure.<\/p>\n\n\n\n
6. What are normalization and denormalization in databases?<\/strong><\/h3>\n\n\n\n\n- Normalization<\/strong><\/a>: Organizing data to reduce redundancy and improve data integrity.
Example: Splitting customer and order details into separate tables and linking them via foreign keys.
<\/li>\n\n\n\n- Denormalization<\/strong>: Combining tables to reduce joins and improve read performance, often used in analytics systems.<\/li>\n<\/ul>\n\n\n\n
7. SQL Coding Question: Write a query to fetch the second highest salary from an “employees” table.<\/strong><\/h3>\n\n\n\nsql\n\nSELECT MAX(salary)\n\nFROM employees\n\nWHERE salary < (SELECT MAX(salary) FROM employees);<\/code><\/pre>\n\n\n\nExplanation:<\/strong><\/p>\n\n\n\n\n- The subquery gets the highest salary.
<\/li>\n\n\n\n - The outer query finds the maximum salary that\u2019s less than that \u2014 effectively, the second highest.<\/li>\n<\/ul>\n\n\n\n
Alternate method using LIMIT (MySQL):<\/p>\n\n\n\n
sql\n\nSELECT DISTINCT salary\n\nFROM employees\n\nORDER BY salary DESC\n\nLIMIT 1 OFFSET 1;<\/code><\/pre>\n\n\n\n8. What is the difference between INNER JOIN and LEFT JOIN in SQL?<\/strong><\/h3>\n\n\n\n\n- INNER JOIN<\/strong>: Returns only matching rows from both tables.<\/li>\n\n\n\n
- LEFT JOIN<\/strong>: Returns all rows from the left table and matching rows from the right table. If no match, NULLs are returned for the right table columns.
<\/li>\n<\/ul>\n\n\n\nExample:<\/p>\n\n\n\n
sql\n\n-- Inner Join\n\nSELECT * FROM orders\n\nINNER JOIN customers ON orders.customer_id = customers.id;\n\n-- Left Join\n\nSELECT * FROM orders\n\nLEFT JOIN customers ON orders.customer_id = customers.id;<\/code><\/pre>\n\n\n\nUse LEFT JOIN<\/strong> when you want all records from one table, even if related records don\u2019t exist in the other.<\/p>\n\n\n\n9. What are primary keys and foreign keys?<\/strong><\/h3>\n\n\n\n\n- Primary Key<\/strong>: A unique identifier for each record in a table. Cannot be NULL.<\/li>\n\n\n\n
- Foreign Key<\/strong>: A field that creates a relationship between two tables. It refers to a primary key in another table.<\/li>\n<\/ul>\n\n\n\n
Example:<\/p>\n\n\n\n
sql\n\n-- Customers Table\n\nid (Primary Key), name\n\n-- Orders Table\n\nid, customer_id (Foreign Key referencing Customers.id)<\/code><\/pre>\n\n\n\nThis setup ensures referential integrity<\/strong> between tables.<\/p>\n\n\n\n10. What is data warehousing, and why is it important?<\/strong><\/h3>\n\n\n\nA data warehouse<\/strong> is a central repository of integrated data from various sources, structured for querying and analysis.<\/p>\n\n\n\nKey benefits:<\/p>\n\n\n\n
<\/figure>\n\n\n\nData engineering is the discipline of designing, building, and maintaining systems and infrastructure that enable the collection, storage, and processing of large volumes of data efficiently.<\/p>\n\n\n\n
While data science<\/a> is focused on extracting insights from data using statistical methods and machine learning, data engineering is about ensuring that the data is clean, reliable, and accessible for such analysis.<\/p>\n\n\n\n A data pipeline is a set of processes that move data from one system to another \u2014 typically from a data source (like an API or database) to a storage or analytics system.<\/p>\n\n\n\n It usually involves:<\/p>\n\n\n\n ETL stands for Extract, Transform, Load<\/strong> \u2014 a traditional process used to prepare data for analysis.<\/p>\n\n\n\n Here are the main types:<\/p>\n\n\n\n Each is suited for specific use cases based on performance, scalability, and structure.<\/p>\n\n\n\n Explanation:<\/strong><\/p>\n\n\n\n Alternate method using LIMIT (MySQL):<\/p>\n\n\n\n Example:<\/p>\n\n\n\n Use LEFT JOIN<\/strong> when you want all records from one table, even if related records don\u2019t exist in the other.<\/p>\n\n\n\n Example:<\/p>\n\n\n\n This setup ensures referential integrity<\/strong> between tables.<\/p>\n\n\n\n A data warehouse<\/strong> is a central repository of integrated data from various sources, structured for querying and analysis.<\/p>\n\n\n\n Key benefits:<\/p>\n\n\n\n2. What is a Data Pipeline?<\/strong><\/h3>\n\n\n\n
\n
3. Explain the ETL process.<\/strong><\/h3>\n\n\n\n
<\/figure>\n\n\n\n\n
4. What is the difference between OLTP and OLAP systems?<\/strong><\/h3>\n\n\n\n
\n
<\/strong>\n\n
<\/li>\n<\/ul>\n<\/li>\n\n\n\n
<\/strong>\n\n
5. What are the different types of databases used in data engineering?<\/strong><\/h3>\n\n\n\n
\n
<\/li>\n\n\n\n
\n\n
<\/li>\n<\/ul>\n<\/li>\n\n\n\n
<\/li>\n\n\n\n6. What are normalization and denormalization in databases?<\/strong><\/h3>\n\n\n\n
\n
Example: Splitting customer and order details into separate tables and linking them via foreign keys.
<\/li>\n\n\n\n7. SQL Coding Question: Write a query to fetch the second highest salary from an “employees” table.<\/strong><\/h3>\n\n\n\n
sql\n\nSELECT MAX(salary)\n\nFROM employees\n\nWHERE salary < (SELECT MAX(salary) FROM employees);<\/code><\/pre>\n\n\n\n\n
<\/li>\n\n\n\nsql\n\nSELECT DISTINCT salary\n\nFROM employees\n\nORDER BY salary DESC\n\nLIMIT 1 OFFSET 1;<\/code><\/pre>\n\n\n\n8. What is the difference between INNER JOIN and LEFT JOIN in SQL?<\/strong><\/h3>\n\n\n\n
\n
<\/li>\n<\/ul>\n\n\n\nsql\n\n-- Inner Join\n\nSELECT * FROM orders\n\nINNER JOIN customers ON orders.customer_id = customers.id;\n\n-- Left Join\n\nSELECT * FROM orders\n\nLEFT JOIN customers ON orders.customer_id = customers.id;<\/code><\/pre>\n\n\n\n9. What are primary keys and foreign keys?<\/strong><\/h3>\n\n\n\n
\n
sql\n\n-- Customers Table\n\nid (Primary Key), name\n\n-- Orders Table\n\nid, customer_id (Foreign Key referencing Customers.id)<\/code><\/pre>\n\n\n\n10. What is data warehousing, and why is it important?<\/strong><\/h3>\n\n\n\n
![\"Data](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/03\/Data-Engineering-Interview-Questions-and-Answers_-Intermediate-Level-1200x630.webp\" "\\"\\"")
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