EPAM Systems Interview Questions and Answers for Freshers

A situational based question

Q1. Print the count of words in a list
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Q2. Check if strings are anagrams
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Q1. Family details were asked
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Q2. Situational based questions were asked
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Java, selenium, API MCQ's

Q1. All manual Testing question
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Q2. Basic to advance java question
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Q3. API and selenium questions
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Q1. All manual testing questions
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Q2. Java, selenium, API
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They will share some basic questions, example, find minimum and maximum value from the given list

Q1. Scenario based question for testing
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Q2. Test plan, test startergy
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Q1. Tell about searching algorithms
Ans. 
Searching algorithms are methods for finding specific data within a structure, like arrays or databases.
• Linear Search: Checks each element sequentially. Example: Finding a number in an unsorted list.

• Binary Search: Efficiently finds an item in a sorted array by repeatedly dividing the search interval in half. Example: Searching in a sorted list.

• Depth-First Search (DFS): Explores as far as possible along each branch befo...read more
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Q2. Write sql query
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SQL queries are used to interact with databases, allowing for data retrieval, manipulation, and management through structured commands.
• SELECT Statement: Used to retrieve data from a database. Example: SELECT * FROM users;

• WHERE Clause: Filters records based on specified conditions. Example: SELECT * FROM users WHERE age > 18;

• JOIN Operations: Combines rows from two or more tables based on a related column. Example: SE...read more
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Q1. Lineage graph,rdd,python decorators,python dict problem,sql self join probelm
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Q2. Types of transformations,no of jobs,tasks,actions
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The question is asking about types of transformations, number of jobs, tasks, and actions in the context of a Senior Data Engineer role.
• Types of transformations: Extract, Transform, Load (ETL), MapReduce, Spark transformations, SQL transformations

• Number of jobs: Depends on the complexity and scale of the data engineering projects

• Number of tasks: Varies based on the number of data sources, data transformations, and data...read more
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Q3. Fact,dimesnion,star and snowflake schema
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Q4. Architecture of spark,airflow,bigquery,
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Spark is a distributed processing engine, Airflow is a workflow management system, and BigQuery is a fully managed data warehouse.
• Spark is designed for big data processing and provides in-memory computation capabilities.

• Airflow is used for orchestrating and scheduling data pipelines.

• BigQuery is a serverless data warehouse that allows for fast and scalable analytics.

• Spark can be integrated with Airflow to schedule and m...read more
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Q5. Optimisation in spark,sql,bigquery,airflow
Ans. 
Optimization techniques in Spark, SQL, BigQuery, and Airflow.
• Use partitioning and bucketing in Spark to optimize data processing.

• Optimize SQL queries by using indexes, query rewriting, and query optimization techniques.

• In BigQuery, use partitioning and clustering to improve query performance.

• Leverage Airflow's task parallelism and resource allocation to optimize workflow execution.
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Q6. Delete duplicates from table in spark and sql
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To delete duplicates from a table in Spark and SQL, you can use the DISTINCT keyword or the dropDuplicates() function.
• In SQL, you can use the DISTINCT keyword in a SELECT statement to retrieve unique rows from a table.

• In Spark, you can use the dropDuplicates() function on a DataFrame to remove duplicate rows.

• Both methods compare all columns by default, but you can specify specific columns to consider for duplicates.

• You...read more
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Q7. Coaelesce,repartition,shuffling,CDC,acid properties,CDC types
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Q1. Dataflow vs Dataproc, layering processing and curated environments in gcp , Data cleaning
Ans. 
Dataflow and Dataproc are both processing services in GCP, but with different approaches and use cases.
• Dataflow is a fully managed service for executing batch and streaming data processing pipelines.

• Dataproc is a managed Spark and Hadoop service for running big data processing and analytics workloads.

• Dataflow provides a serverless and auto-scaling environment, while Dataproc offers more control and flexibility.

• Dataflow...read more
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Q1. Pyspark field delimited questions with group by transformations, Sql window function question Discussion on arch of spark,bq,airflow. How to define dependency between tasks and two diff dags. star and sno...read more
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This was final round with Client.
They ask questions based on my work in pyspark area.
Questions are like:
What kind of transformations you used.
Broadcast join internals.
Spark internal joins
Spark catalyst optimizer.What are the joins happens in catalyst optimizer.
Window function question: 3rd highest salary of an emp
Discussion on airflow arch and how to deploy a airflow dag in gcp.
Discussion on BQ on what kind of work i have done till now.

Q1. Techincal coding question
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Q2. Project related questions
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Q1. Generic project duscussion and salary
Ans. 
Discussing project details and negotiating salary for Senior Developer position.
• Highlighting past project successes and challenges

• Discussing technical skills and experience relevant to the role

• Negotiating salary based on market rates and personal expectations
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