kipi.ai Data Engineer Interview Questions and Answers

Coding round had one SQL and one Python question. And some mcqs around python and math

Q1. It was on store and products querying with SQL
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Q2. Same questions were asked in Python
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Q1. It was a techno-managerial round with some guesstimates and about my recent projects
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Q1. Java questions and data engineering
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It was a written test where theoretical SQL questions were asked like primary key, foreign key, set operators and some queries

Q1. All SQL Concepts like Join, normalization, trigger, stored procedure, keys, drop truncate del difference, where having difference, Aggregate scaler window functions, fetch duplicate records query, acid pro...read more
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Two coding questions

Q1. DBMS questions, keys
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Q2. SQL related queries
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Q1. Testing concepts STLC
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Q2. Java code to reverse a string
Ans. 
Java code to reverse a string
• Use StringBuilder class to reverse the string

• Call reverse() method on the StringBuilder object

• Convert the StringBuilder object back to String using toString() method
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Q1. Agile concepts like sprints planning and Jira
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Coding test was bad. they asked irrelevant things that were not related to the field

Q1. What is data engineering
Ans. 
Data engineering is the process of designing, building, and maintaining the infrastructure for data storage and processing.
• Data engineering involves creating and managing data pipelines

• It includes tasks such as data modeling, data integration, and data warehousing

• Data engineers work with big data technologies such as Hadoop, Spark, and NoSQL databases

• They also ensure data quality, security, and scalability

• Examples of d...read more
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Q2. What is resilient distributed database
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A resilient distributed database is a database that can continue to function even if some of its nodes fail.
• It is designed to be fault-tolerant and highly available.

• Data is distributed across multiple nodes to ensure redundancy.

• If one node fails, the database can continue to function using data from other nodes.

• Examples include Apache Cassandra, Riak, and HBase.
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Q1. Describe your workflow of the last project
Ans. 
Developed ETL pipeline to ingest, clean, and analyze customer data for personalized marketing campaigns
• Gathered requirements from stakeholders to understand data sources and business objectives

• Designed data model to store customer information and campaign performance metrics

• Implemented ETL process using Python and Apache Spark to extract, transform, and load data

• Performed data quality checks and created visualizations ...read more
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Q2. What are the different transformations you have used
Ans. 
I have used various transformations such as filtering, joining, aggregating, and pivoting in my data engineering projects.
• Filtering data based on certain conditions

• Joining multiple datasets together

• Aggregating data to summarize information

• Pivoting data from rows to columns or vice versa
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