Colan Infotech Data Engineer Interview Questions and Answers

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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Sql assessment round

Q1. Python gcp biquery airflow dataflow sql
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Q1. Recent projects experience, bigquery, sql
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Q1. Salary discussion
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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
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Q1. HR question and family background
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It was a written test where theoretical SQL questions were asked like primary key, foreign key, set operators and some queries

Q1. All SQL Concepts like Join, normalization, trigger, stored procedure, keys, drop truncate del difference, where having difference, Aggregate scaler window functions, fetch duplicate records query, acid pro...read more
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Two coding questions

Q1. DBMS questions, keys
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Q2. SQL related queries
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Q1. Explain process in adf
Ans. 
ADF stands for Azure Data Factory, a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
• ADF allows you to create data-driven workflows for orchestrating and automating data movement and data transformation.

• You can use ADF to ingest data from various sources, process and transform the data, and then publish the data to different destinations.

• ADF supports a wide range of d...read more
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Q1. Testing concepts STLC
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Q2. Java code to reverse a string
Ans. 
Java code to reverse a string
• Use StringBuilder class to reverse the string

• Call reverse() method on the StringBuilder object

• Convert the StringBuilder object back to String using toString() method
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Q1. Agile concepts like sprints planning and Jira
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Q1. Describe your workflow of the last project
Ans. 
Developed ETL pipeline to ingest, clean, and analyze customer data for personalized marketing campaigns
• Gathered requirements from stakeholders to understand data sources and business objectives

• Designed data model to store customer information and campaign performance metrics

• Implemented ETL process using Python and Apache Spark to extract, transform, and load data

• Performed data quality checks and created visualizations ...read more
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Q2. What are the different transformations you have used
Ans. 
I have used various transformations such as filtering, joining, aggregating, and pivoting in my data engineering projects.
• Filtering data based on certain conditions

• Joining multiple datasets together

• Aggregating data to summarize information

• Pivoting data from rows to columns or vice versa
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