10+ Celebal Technologies Data Engineer Interview Questions and Answers

Celebal Technologies is a technology company specializing in data engineering and analytics solutions.

• Celebal Technologies is known for providing data engineering and analytics solutions.

• They offer services such as data integration, data warehousing, and data visualization.

• Celebal Technologies works with clients across various industries to help them optimize their data processes.

• They have expertise in technologies like Hadoop, Spark, and Python for data engineering.

• The compa...read more

Celebal Technologies aims to provide innovative solutions using cutting-edge technologies to help businesses thrive in the digital age.

• Developing advanced data analytics tools for businesses

• Creating AI-driven solutions for automation and optimization

• Offering consulting services for digital transformation

• Empowering organizations with cloud computing and IoT solutions

The WHERE clause is used to filter rows before grouping, while the HAVING clause is used to filter groups after grouping.

• WHERE clause is used with SELECT, UPDATE, and DELETE statements.

• HAVING clause is used with SELECT statements that include GROUP BY clause.

• WHERE clause filters individual rows based on conditions.

• HAVING clause filters groups based on conditions.

• WHERE clause is applied before the GROUP BY clause.

• HAVING clause is applied after the GROUP BY clause.

• WHERE clause ...read more

I have extensive experience in using Pyspark and Python for data engineering tasks.

• I have worked on various projects involving data processing, transformation, and analysis using Pyspark and Python.

• I am proficient in writing efficient and optimized code in Pyspark for big data processing.

• I have experience in handling large datasets and implementing complex data pipelines using Pyspark and Python.

Advanced types of join include outer join, self join, and cross join.

• Outer join: includes unmatched rows from one or both tables

• Self join: joins a table with itself

• Cross join: combines each row from one table with each row from another table

Python data structures are containers that hold and organize data in different ways.

• Some common Python data structures are lists, tuples, sets, and dictionaries.

• Lists are ordered and mutable, allowing duplicate elements.

• Tuples are ordered and immutable, useful for storing related data together.

• Sets are unordered and contain unique elements, useful for mathematical operations.

• Dictionaries are key-value pairs, providing fast access to values based on keys.

Joins are used to combine rows from two or more tables based on a related column between them.

• Joins are used in SQL to retrieve data from multiple tables based on a related column between them.

• Common types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

• Subqueries are queries nested within another query, typically used to return a single value or a list of values for comparison.

The difference between the difference is the result of subtracting one value from another.

• Difference is the result of subtracting two values.

• The difference between two values can be positive, negative, or zero.

• For example, the difference between 10 and 5 is 5.

Use bitwise operations to multiply two numbers without using '*' operator.

• Use bitwise shift left operation to multiply a number by 2.

• Add the result of shifting left n times for the second number.

• Example: 3 * 5 = 3 << 2 + 3 = 12.

Indexing in SQL is a technique used to improve the performance of queries by creating a data structure that allows for faster retrieval of data.

• Indexes are created on columns in a database table to speed up the retrieval of data.

• They work similar to the index in a book, allowing the database to quickly find the rows that match a certain condition.

• Indexes can be created using a single column or a combination of columns.

• Examples: CREATE INDEX index_name ON table_name(column_nam...read more

ETL is Extract, Transform, Load where data is extracted, transformed, and loaded in that order. ELT is Extract, Load, Transform where data is extracted, loaded, and then transformed.

• ETL: Data is extracted from the source, transformed in a separate system, and then loaded into the target system.

• ELT: Data is extracted from the source, loaded into the target system, and then transformed within the target system.

• ETL is suitable for scenarios where data needs to be transformed bef...read more

Join combines rows from two or more tables based on a related column, while union combines rows from two or more tables into a single result set.

• Join is used to combine rows from different tables based on a related column.

• Union is used to combine rows from two or more tables into a single result set.

• Join can be used with different types like inner join, left join, right join, etc.

• Union only combines rows with the same number of columns and compatible data types.

• Join can inclu...read more

Use SQL query with joins, common table expressions (CTE) and Azure Data Factory (ADF) to find the 2nd highest number.

• Use a SQL query with joins to combine the necessary tables or datasets.

• Utilize common table expressions (CTE) to simplify the query and make it more readable.

• Leverage Azure Data Factory (ADF) to automate the process of running the query and retrieving the result.

• Order the numbers in descending order and select the second row to find the 2nd highest number.

Find the repeating element in a list

• Iterate through the list and keep track of elements seen so far

• Use a hash set to efficiently check for duplicates

• Return the first element that is already in the set

Use the MAX() function in SQL to calculate the maximum salary.

• Use the MAX() function along with the column name of the salary field.

• Example: SELECT MAX(salary) FROM employees;

• Ensure the correct table and column names are used in the query.