Teksolto Software Interview Questions and Answers

Q1. Tell me about yourself?
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Q2. Why ADP?
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Q1. What do you know about SQL?
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Q2. How can you write a query to retrieve details from two tables and present them in a single table format?
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Q3. What is the SQL query to retrieve the number of students grouped by their respective streams?
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Q1. More of your day to day activities as an engineering manager
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Q2. Status reporting, Matrices EM should maintain,Risks and Mitigations , Conflict Resolution,
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Q1. System Architecture
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Q2. Basic Java collections like streams, collections , garbage collection , spring boot basic working
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Q1. Team management
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Q2. Project execution
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Thirty-nine questions, including two coding challenges and three to four sets of games.

Q1. What is dynamic dispatch?
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Q2. How do u manage stress?
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Q3. What are environment variables in linux?
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Q4. Explian merge sort.
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Q1. Machine learning questions
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Q2. Decision trees, random forest
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Q1. ML Ops related questions
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Q1. 1 hr interview divided into 4 sections - Intro - Backend - .NET & OOPS Concepts (Was given a code to analyze) - SQL - Write a sql query & some sql questions on joins etc. - Frontend - Angular related quest...read more
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Q1. Bit low level Design Patterns Questions, SQL Questions, Angular Questions Checking your confidence while answering
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Q1. This was Manegerial Round, asked about projects worked upon and some questions over the projects
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Q1. For this round I was being called to their base location. Salary Discussion
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The coding questions were at Leetcode difficulty level and were derived from the Striver sheet.

Q1. BFS graph level
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Q2. Minimum flight distance . I was not shortlisted for interview.
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Basic Python, SQL, and Bash questions

Q1. SQL questions with operations that include changing from string to array. Tip: stick to RDBMS-specific dialects only (like Postgres), I used Spark SQL
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Q2. Simple Python questions with a follow-up to optimise it
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Q3. Bash script-based questions, are pretty basic.
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Q4. Data pipeline design and best practices.
Ans. 
Data pipeline design involves creating a system to efficiently collect, process, and analyze data.
• Understand the data sources and requirements before designing the pipeline.

• Use tools like Apache Kafka, Apache NiFi, or AWS Glue for data ingestion and processing.

• Implement data validation and error handling mechanisms to ensure data quality.

• Consider scalability and performance optimization while designing the pipeline.

• Doc...read more
Answered by AI
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Q1. Easy to medium Leetcode-based question. With moderate difficulty.
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Q2. Simple Python-based question with optimisation.
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Q3. Design specific questions based on Data pipelines.
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Q1. SQL-based question with moderate difficulty.
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Q2. Python-based questions, follow questions with some optimisations.
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Q3. Bash-script based round.
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