Random Trees Interview Questions and Answers for Experienced

It wa really a great experience.

It was really a great experience.

Q1. Where do you see yourself after 3 years?
Ans. 
In 3 years, I see myself leading a team of data engineers, implementing cutting-edge technologies, and driving impactful data-driven decisions.
• Leading a team of data engineers

• Implementing cutting-edge technologies

• Driving impactful data-driven decisions
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Q2. What are your strenghts?
Ans. 
My strengths include strong analytical skills, attention to detail, and the ability to work well in a team.
• Strong analytical skills - able to analyze complex data sets and derive meaningful insights

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

• Team player - collaborate effectively with colleagues to achieve common goals
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Q1. What projects you have worked upon?
Ans. 
I have worked on projects involving building data pipelines, optimizing database performance, and creating machine learning models.
• Built data pipelines using Apache Spark and Kafka

• Optimized database performance by tuning queries and indexes

• Created machine learning models for predictive analytics

• Implemented real-time data processing using technologies like Apache Flink
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Q2. What is your CGPA?
Ans. 
My CGPA is 3.8 out of 4.0.
• My CGPA is 3.8, which is considered high in my university.

• I have consistently maintained a high CGPA throughout my academic career.

• I have received several academic awards based on my CGPA.

• My CGPA reflects my dedication and hard work towards my studies.
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Q3. What are your hobbies?
Ans. 
My hobbies include hiking, photography, and playing the guitar.
• Hiking: I enjoy exploring nature trails and challenging myself physically.

• Photography: I love capturing moments and landscapes through my camera lens.

• Playing the guitar: I find relaxation and creativity in strumming chords and learning new songs.
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This was my first campus drive,& it was one of the hardest one too.We had 3 coding problems for 60 mins.It was held on HackerRank & it was not so hard but not so easy for the beginners.
1)Lambda Sort
2) and 3) ques on SQL
It was different ques for each one.

Q1. The interviewer asked all the concepts of pyspark, ETL and a code on dsa
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Easy and moderate level question

Given a relevant topic and discussion on it

Q1. Introducd yourself
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Q2. Why do you want to join us
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Reasoning and aptitude questions were asked

Q1. Interview was around python programming and team fitment
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It was a coding round with sql ,python questions , few aptitude questions

Q1. They asked few questions sql and python and few questions - depending on the role
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Q2. BASIC SQL WHAT YOU HAD WRITTEN IN THE CODE
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Q1. They asked me few questions related to sql
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Q2. BASIC PYTHON QUESTIONS LIKE WHAT YOU HAVE WRITTEN IN THE CODE
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Q1. About yourself , your hobby etc
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Python and SQL questions were asked

Q1. I was asked about the project
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Q1. ACID properties of DBMS
Ans. 
ACID properties ensure data integrity in DBMS: Atomicity, Consistency, Isolation, Durability.
• Atomicity ensures that all operations in a transaction are completed successfully or none at all.

• Consistency ensures that the database remains in a consistent state before and after the transaction.

• Isolation ensures that multiple transactions can be executed concurrently without affecting each other.

• Durability ensures that once...read more
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Q1. HR question and family background
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Q1. BigQuery Architecture and file formats
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Q2. Airflow operators and what is the use of Airflow python operator
Ans. 
Airflow operators are used to define tasks in a workflow. The Airflow Python operator is used to execute Python functions as tasks.
• Airflow operators are used to define individual tasks in a workflow

• The Airflow Python operator is specifically used to execute Python functions as tasks

• It allows for flexibility in defining custom tasks using Python code

• Example: PythonOperator(task_id='my_task', python_callable=my_python_fu
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Q1. Explain the entire ETL workload in your current company project and how to handle the data quality issues.
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