Brillio Data Engineer Interview Questions and Answers

Q1. Data warehousing related questions
Add your answer
Q2. SQL scenario based questions
Add your answer
Q3. Project experience
Ans. 
I have experience working on projects involving data pipeline development, ETL processes, and data warehousing.
• Developed ETL processes to extract, transform, and load data from various sources into a data warehouse

• Built data pipelines to automate the flow of data between systems and ensure data quality and consistency

• Optimized database performance and implemented data modeling best practices

• Worked on real-time data pro...read more
Answered by AI
Add your answer
Q4. Python Based questions
Add your answer
Q5. AWS features and questions
Add your answer

Q1. Similar to first round but in depth questions relatively
Add your answer
Q2. Asked about career goals and stuff
Add your answer

Q1. General work related conversation
Add your answer
Q2. Salary discussion
Add your answer

Q1. SCD questions. Iceberg questions
Add your answer
Q2. Basic python programing, pyspark architechture.
Add your answer

Q1. Questions on Pyspark
Add your answer
Q2. Questions on SQL
Add your answer
Q3. Transformations
Add your answer
Q4. Questions on Sql optimizations
Add your answer
Q5. Questions About my current Project
Add your answer

Q1. Incremental load in pyspark
Ans. 
Incremental load in pyspark refers to loading only new or updated data into a dataset without reloading the entire dataset.
• Use the 'delta' function in pyspark to perform incremental loads by specifying the 'mergeSchema' option.

• Utilize the 'partitionBy' function to optimize incremental loads by partitioning the data based on specific columns.

• Implement a logic to identify new or updated records based on timestamps or uni...read more
Answered by AI
Add your answer
Q2. Drop duplicates
Add your answer

Q1. Data Structures
Add your answer
Q2. Python Lambda Function
Add your answer

Q1. What are your Strengths
Ans. 
My strengths include strong analytical skills, attention to detail, and problem-solving abilities.
• Strong analytical skills - able to analyze complex data sets and derive meaningful insights

• Attention to detail - meticulous in ensuring data accuracy and quality

• Problem-solving abilities - adept at identifying and resolving data-related issues

• Experience with data manipulation tools like SQL, Python, and Spark
Answered by AI
Add your answer
Q2. Why you are looking for job change
Ans. 
Seeking new challenges and growth opportunities in a different environment.
• Looking for new challenges to enhance my skills and knowledge

• Seeking growth opportunities that align with my career goals

• Interested in exploring different technologies and industries

• Want to work in a more collaborative team environment

• Seeking better work-life balance or location proximity
Answered by AI
Add your answer

Q1. What is Pyspark?
Ans. 
Pyspark is a Python API for Apache Spark, a powerful open-source distributed computing system.
• Pyspark is used for processing large datasets in parallel across a cluster of computers.

• It provides high-level APIs in Python for Spark programming.

• Pyspark allows seamless integration with other Python libraries like Pandas and NumPy.

• Example: Using Pyspark to perform data analysis and machine learning tasks on big data sets.
Answered by AI
Add your answer
Q2. What is Pyspark SQL?
Ans. 
Pyspark SQL is a module in Apache Spark that provides a SQL interface for working with structured data.
• Pyspark SQL allows users to run SQL queries on Spark dataframes.

• It provides a more concise and user-friendly way to interact with data compared to traditional Spark RDDs.

• Users can leverage the power of SQL for data manipulation and analysis within the Spark ecosystem.
Answered by AI
Add your answer
Q3. How to merge 2 dataframes of different schema?
Ans. 
To merge 2 dataframes of different schema, use join operations or data transformation techniques.
• Use join operations like inner join, outer join, left join, or right join based on the requirement.

• Perform data transformation to align the schemas before merging.

• Use tools like Apache Spark, Pandas, or SQL to merge dataframes with different schemas.
Answered by AI
Add your answer
Q4. What is Pyspark streaming?
Ans. 
Pyspark streaming is a scalable and fault-tolerant stream processing engine built on top of Apache Spark.
• Pyspark streaming allows for real-time processing of streaming data.

• It provides high-level APIs in Python for creating streaming applications.

• Pyspark streaming supports various data sources like Kafka, Flume, Kinesis, etc.

• It enables windowed computations and stateful processing for handling streaming data.

• Example: C...read more
Answered by AI
Add your answer

Just focus on the basics of pyspark.