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I applied via Campus Placement and was interviewed before Nov 2023. There were 2 interview rounds.
Development Related task.
I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.
Query to find the second highest salary from a table
Use the ORDER BY clause to sort the salaries in descending order
Use the LIMIT clause to retrieve the second row
Remove duplicates from a list without using inbuilt functions
Create an empty list to store unique items
Iterate through the original list and add items to the new list if they are not already present
Return the new list with duplicates removed
I have a strong background in data engineering with proven experience in designing and implementing scalable data solutions.
I have a solid understanding of data modeling, ETL processes, and data warehousing.
I have experience working with various databases such as SQL, NoSQL, and cloud-based solutions like AWS Redshift.
I am proficient in programming languages like Python, Java, and Scala for data processing and analysis...
Seeking new challenges and growth opportunities.
Desire for career advancement
Looking for new challenges
Seeking better work-life balance
Relocation to a different city
Company restructuring or downsizing
I applied via Company Website and was interviewed before Nov 2021. There were 3 interview rounds.
They mostly ask about data science related questions on Pandas
They ask List Dictionary and String related questions.
I applied via Campus Placement and was interviewed before Jul 2020. There was 1 interview round.
I applied via Walk-in and was interviewed before Feb 2020. There was 1 interview round.
Spark has a master-slave architecture with a cluster manager and worker nodes.
Spark has a driver program that communicates with a cluster manager to allocate resources and schedule tasks.
The cluster manager can be standalone, Mesos, or YARN.
Worker nodes execute tasks and store data in memory or on disk.
Spark can also utilize external data sources like Hadoop Distributed File System (HDFS) or Amazon S3.
Spark supports va...
Basic Questions on python related to strings
Choosing the right technology depends on the specific requirements of the situation.
Consider the data size and complexity
Evaluate the processing speed and scalability
Assess the cost and availability of the technology
Take into account the skillset of the team
Examples: Hadoop for big data, Spark for real-time processing, AWS for cloud-based solutions
EMR is a managed Hadoop framework for processing large amounts of data, while EC2 is a scalable virtual server in AWS.
EMR stands for Elastic MapReduce and is a managed Hadoop framework for processing large amounts of data.
EC2 stands for Elastic Compute Cloud and is a scalable virtual server in Amazon Web Services (AWS).
EMR allows for easy provisioning and scaling of Hadoop clusters, while EC2 provides resizable compute...
I have experience working with both Star and Snowflake schemas in my projects.
Star schema is a denormalized schema where one central fact table is connected to multiple dimension tables.
Snowflake schema is a normalized schema where dimension tables are further normalized into sub-dimension tables.
Used Star schema for simpler, smaller datasets where performance is a priority.
Used Snowflake schema for complex, larger dat...
Yes, I have used Python and PySpark in my projects for data engineering tasks.
I have used Python for data manipulation, analysis, and visualization.
I have used PySpark for big data processing and distributed computing.
I have experience in writing PySpark jobs to process large datasets efficiently.
Yes, I have experience with serverless schema.
I have worked with AWS Lambda to build serverless applications.
I have experience using serverless frameworks like Serverless Framework or AWS SAM.
I have designed and implemented serverless architectures using services like AWS API Gateway and AWS DynamoDB.
Databricks is a unified analytics platform that provides a collaborative environment for data scientists, engineers, and analysts.
Databricks is built on top of Apache Spark, providing a unified platform for data engineering, data science, and business analytics.
Internals of Databricks include a cluster manager, job scheduler, and workspace for collaboration.
Optimization techniques in Databricks include query optimizati...
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