Atos Senior Data Engineer Interview Questions and Answers

Q1. All questions based on databricks and some pyspark , python , SQL only.
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Q2. Learn windows function implementation in databricks note book.
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Q1. This round about your salary discussion around.
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Q1. Windows function-related questions.
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Q2. Join Related Questions.
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Q1. Join related Questions
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Q2. Subqueries related queations.
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Python and sql tasks

Q1. Project related questions
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Q2. Coding questions on pyspark windows
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Q1. Managerial discussions, mostly in and around the previous projects
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Q1. Coding in pyspark
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Pyspark is a Python library for big data processing using Spark framework.
• Pyspark is used for processing large datasets in parallel.

• It provides APIs for data manipulation, querying, and analysis.

• Example: Using pyspark to read a CSV file and perform data transformations.
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Q2. Databricks optimisation technique
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Databricks optimisation techniques improve performance and efficiency of data processing on the Databricks platform.
• Use cluster sizing and autoscaling to optimize resource allocation based on workload

• Leverage Databricks Delta for optimized data storage and processing

• Utilize caching and persisting data to reduce computation time

• Optimize queries by using appropriate indexing and partitioning strategies
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Q3. Aqe details in databricks
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Databricks is a unified data analytics platform that provides a collaborative environment for data engineers.
• Databricks is built on top of Apache Spark and provides a workspace for data engineering tasks.

• It allows for easy integration with various data sources and tools for data processing.

• Databricks provides features like notebooks, clusters, and libraries for efficient data engineering workflows.
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Q1. Adf,etl,python,adb
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Q1. More questions on spark and java
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Q2. More questions on sql
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Q1. Over all project architecture
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Q2. Sample data and its transformations
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Sample data and its transformations
• Sample data can be in the form of CSV, JSON, or database tables

• Transformations include cleaning, filtering, aggregating, and joining data

• Examples: converting date formats, removing duplicates, calculating averages
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Q1. Why are u leaving current job
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Seeking new challenges and opportunities for growth in a more dynamic environment.
• Looking for new challenges and opportunities for growth

• Seeking a more dynamic work environment

• Interested in expanding skill set and knowledge

• Want to work on more innovative projects
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Q1. Explain about yourself.
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I am a Senior Data Engineer with 5+ years of experience in designing and implementing data pipelines for large-scale projects.
• Experienced in ETL processes and data warehousing

• Proficient in programming languages like Python, SQL, and Java

• Skilled in working with big data technologies such as Hadoop, Spark, and Kafka

• Strong understanding of data modeling and database management

• Excellent problem-solving and communication sk
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Q2. Explain about your current project.
Ans. 
Developing a real-time data processing system for analyzing customer behavior on e-commerce platform.
• Utilizing Apache Kafka for real-time data streaming

• Implementing Spark for data processing and analysis

• Creating machine learning models for customer segmentation

• Integrating with Elasticsearch for data indexing and search functionality
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Q3. Big data concept
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Q4. Spark related questions
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Spark Optimization, Transformation, DLT, DL, Data Governance
Python
SQL