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Landmark Group Data Engineer Interview Questions and Answers
Landmark Group Data Engineer Interview Experiences
1 interview found
Anonymous
I applied via Naukri.com and was interviewed in Aug 2024. There was 1 interview round.
(5 Questions)
- Q1. Wxaplinnyour project
- Q2. How would you build a pipeline to connect http source and bring data in adls
- Ans.
Build a pipeline to connect http source and bring data in adls
Set up a data ingestion tool like Apache NiFi or Azure Data Factory to pull data from the http source
Transform the data as needed using tools like Apache Spark or Azure Databricks
Store the data in Azure Data Lake Storage (ADLS) for further processing and analysis
- Q3. Dimension and fact tabel difference
- Ans.
Dimension tables store descriptive attributes while fact tables store quantitative data.
Dimension tables contain attributes that describe the business entities, such as customer, product, or time.
Fact tables contain quantitative data or metrics that are typically numeric and additive, such as sales revenue or quantity sold.
Dimension tables are denormalized and have a one-to-many relationship with fact tables.
Fact table...
- Q4. Write slq query to get employee having 2manager
- Ans.
Use a self join to find employees with 2 managers in SQL query.
Use a self join on the employee table to join the table with itself.
Count the number of distinct managers for each employee.
Filter the results to only include employees with 2 managers.
- Q5. Get second highest salary usingSQL
Skills evaluated in this interview
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I applied via Company Website and was interviewed in Aug 2024. There was 1 interview round.
(5 Questions)
- Q1. It was hiring drive face to face interview
- Q2. Project related indepth discussions
- Q3. Medium level SQL and DSA
- Q4. Sorting colors DSA problem
- Ans.
Sort an array of colors in a specific order
Use a custom sorting function to sort the colors based on a predefined order
Map each color to a numerical value and sort based on that value
Consider using a hashmap to store the order of colors
- Q5. In depth spark optimization question
Interview Preparation Tips
Skills evaluated in this interview
Selected
I applied via LinkedIn and was interviewed in Sep 2024. There were 2 interview rounds.
(2 Questions)
- Q1. Data Structures
- Q2. Algorithms concepts
(2 Questions)
- Q1. Data Engineering Concepts
- Q2. Spark and pyspark
I applied via LinkedIn and was interviewed in Sep 2023. There were 2 interview rounds.
(2 Questions)
- Q1. Python coding, SQL theoretical
- Q2. SPARK working question
Interview Preparation Tips
Sql questions and python logics
(2 Questions)
- Q1. About sql and python
- Q2. Hadoop and kinit
Selected
I applied via Naukri.com and was interviewed in Aug 2023. There was 1 interview round.
(1 Question)
- Q1. About partitions and bucketing Spark optimization Question from hadoop All questions were scenario based
I applied via Company Website and was interviewed in May 2024. There was 1 interview round.
(1 Question)
- Q1. Clueless and very rude interviewer. The troglodyte asked only from my past experience and everything not included either in the job description or my resume.
Ankita Gulati
Based on python and sql
(2 Questions)
- Q1. Related to spark
- Q2. Dimensional Modelling
I applied via Approached by Company and was interviewed in Jul 2022. There were 4 interview rounds.
(1 Question)
- Q1. I was asked medium Data structure questions mainly on Arrays and strings.
(1 Question)
- Q1. This round was basically on big data concepts, interviewer asked about Hive, Hbase, Spark and SQL.
(1 Question)
- Q1. This was a managerial round mostly focused on technical part for the first half, than some bit on optimisation of Big data application as well as infra overall. Than some basic managerial questions.
(1 Question)
- Q1. This round was about basic HR questions, such as why Target, salary discussion etc.
Interview Preparation Tips
- Spark
- Hive
- Airflow
- Data Structures
- SCALA
- Python
- API
I applied via Approached by Company and was interviewed in Jun 2024. There was 1 interview round.
(1 Question)
- Q1. Static allocation in spark. 10TB of file needs to be processed in spark, what configuration (executors and cores) would you choose and why?
- Ans.
For processing 10TB of file in Spark, consider allocating multiple executors with sufficient cores to maximize parallel processing.
Allocate multiple executors to handle the large file size efficiently
Determine the optimal number of cores per executor based on the available resources and workload
Consider the memory requirements for each executor to avoid out-of-memory errors
Adjust the configuration based on the specific
Skills evaluated in this interview
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