GE Healthcare Data Engineer Interview Questions and Answers

Q1. SQL related questions on snowflake and databricks
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Q1. Database architecture and design related questions
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Q1. Databricks experience, domain knowledge and mostly experience related questions.
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Q1. Expectations and how you would be a good fit. All general HR questions that you can find
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Q1. Basic C# and oops questions , mostly on inheritance , abstraction ,encapsulation , properties
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Q2. Coding questions related to strings finding longest substring without repeating characters , find the count of vowels in string with using dictionary kr hash ( used ascii value approach)
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Q1. Mostly on project .
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Q2. Was asked about design patterns , had to create a design for a simple . How would I structure all the folders classes , interfaces logics etc .
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Q1. Self introduction
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Q2. Preferences in life about your studies
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Q1. Studies based from your overall whole randomly topic wise Qs
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Q2. Base on your studies
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Group discussion was amazing not to muuch difficult but based on anylitical or logical questions based
GD surrounds was lite not stressed.
Some hobbies question round

Must everyone to speak atleast on one question

Q1. Type of Filters in Tableau.
Ans. 
Tableau offers various types of filters including quick filters, context filters, and data source filters.
• Quick filters allow users to easily filter data by selecting values from a list.

• Context filters are applied before other filters, affecting the data visible to subsequent filters.

• Data source filters limit the data available to Tableau by filtering data at the data source level.

• Other types of filters include extract...read more
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Q2. Types of refresh in Tableau
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There are two types of refresh in Tableau: Extract Refresh and Data Source Refresh.
• Extract Refresh: Refreshes the data in Tableau extract, which is a snapshot of data from the original data source.

• Data Source Refresh: Refreshes the data directly from the original data source.

• Examples: Extract Refresh is useful when working with large datasets to improve performance, while Data Source Refresh ensures real-time data upda
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Q3. Difference in Extract and live connection.
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Extract connection imports data into Tableau workbook while live connection directly connects to data source.
• Extract connection creates a static snapshot of data in Tableau workbook.

• Live connection directly queries data from the source in real-time.

• Extract connection is useful for large datasets or when offline access is needed.

• Live connection is beneficial for real-time data analysis and dynamic updates.

• Example: Extra...read more
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Q1. What is java script?
Ans. 
JavaScript is a high-level, interpreted programming language used for creating interactive websites.
• JavaScript is commonly used for client-side web development.

• It can be used to add interactivity, animations, and dynamic content to websites.

• JavaScript is often used in conjunction with HTML and CSS.

• Popular JavaScript frameworks include React, Angular, and Vue.
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Q1. Explain js , virtual dom?
Ans. 
JS is a programming language used for web development. Virtual DOM is a concept in React to improve performance.
• JS (JavaScript) is a popular programming language used for web development.

• Virtual DOM is a concept in React where a lightweight copy of the actual DOM is created and updated to improve performance.

• Virtual DOM allows React to efficiently update the actual DOM by only re-rendering components that have changed.
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Q1. RDD, Datafram, dataset difference
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Q2. Find the 2nd hightest salary
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Q3. What is ADF in azure
Ans. 
ADF in Azure stands for Azure Data Factory, a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
• Azure Data Factory (ADF) is used to orchestrate and automate data movement and data transformation.

• It supports a wide range of data sources, including Azure Blob Storage, Azure SQL Database, and on-premises data sources.

• ADF allows you to create data pipelines using a visual i...read more
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Basics of C++. Solve some problem by given complexity. Find the bugs in code.

Q1. Question from your last project.
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Q2. Design pattern in C++.
Ans. 
Design patterns in C++ are reusable solutions to common problems in software design.
• Design patterns help in creating flexible, maintainable, and scalable code.

• Examples of design patterns in C++ include Singleton, Factory, Observer, and Strategy.

• Each design pattern has a specific purpose and can be applied in different scenarios.
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