Recent Data Engineer Interview Questions

Anzhe M. - "There are 2 questions popping into my mind: Should the 2nd job have to kick off at 12:30AM? Are there others depending on the 2nd job? If both answers are no, we may simply postpone the second job to allow sufficient time for the first one to complete. If they are yeses, we could let the 2nd job retry to a certain amount of times. Make sure that even reaching the maximum of retries won't delay or fail the following jobs."See full answer

Ramagiri P. - "Medallion architecture is a layered data architecture used in lakehouse systems. Data flows through Bronze, Silver, and Gold layers where each layer improves data quality. Bronze stores raw data, Silver contains cleaned and validated datasets, and Gold provides aggregated business-ready data for analytics and reporting bronzedf = spark.read.json("/landing/apidata") bronze_df.write.format("delta").save("/bronze/users")"See full answer

Nitish C. - "Delta lake is a metadata layer on top of cloud storage which helps giving datalake transactional capabilities. It helps implement upsert/merge as it conforms a schema to the data assets stored in cloud. It also offers various other capabilities like liquid clustering,time travel, schema evolution,deletes."See full answer

Kshitij I. - "Data lake and warehouse are both places that allow an organization to store large amounts of data. When swimming in a lake, one would imagine that they come across all sorts of stuff - floating twigs, fish in the water, stones, chemicals and sometimes may be even a snake. Similarly, a data lake stores all forms of data that the company has without any indexing. The data is available at any time but needs to be first cleaned up and reorganized before it can be used for any type of analysis. A"See full answer

Nitish C. - "All purpose cluster remains up and running for longer duration irrespective of the job hence preferred for notebooks, adhoc work whereas job cluster spins up as per the submitted job and shuts down post the completion hence preferred for production scheduled workloads as it also offers compute isolation"See full answer

Payal B. - "My brute force approach was to read them. Give a id to each paragraph and for each token count the number of time it has appeared. If any two rows look same , it is duplicated. Further , interviewer guided me that he will do it with hashing."See full answer

VContaineers - " Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between: Skipping the current house and taking the maximum money stolen up to the previous house. Robbing the current house and adding its value to the maximum money stolen up to the house two steps back. package main import ( "fmt" ) // rob function calculates the maximum money a robber can steal func maxRob(nums []int) int { ln"See full answer

Lati K. - "I generally struggle with stakeholders and partners who doesn't communicate enough. Now it could be either they don't invest sufficient time and energy in doing so or at times they lack the skill sets to do so. In both the cases, the entire responsibility fell on the other person to dig deep into why someone is doing the way they are doing, reading into patterns and behaviour of their personality and adapting to those communication styles"See full answer

Nicola R. - "You shouldn't hire me if you're looking for someone to simply write code in large volumes without considering the bigger picture. I'm someone who thrives on solving root problems, building, cohesive systems, and ensuring stakeholder alignment. If the priority is speed over thoughtful analysis, I might not be the best fit. However, if you're looking for someone who can drive meaningful and scalable solutions, collaborate effectively, and contribute to long-term success, then I believe I'd bring s"See full answer

Nidhi S. - "There are couple of reasons for it - Kind of role : Its a product manager role loaded with analytical work, So working with data in stringent regulatory guideline make it more exciting and thrilling. Location & industry is like - Cherry on the cake, Bangalore weather and BFI is at its all time peak as people spending behavior is changing continuously, it will be interesting to see big giants like visa are managing it."See full answer

Joshua R. - "Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"See full answer