Data Pipeline Design Interview Questions

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Asked at Databricks • 6 months ago
Design a document processing pipeline.
Software Engineer
Data Pipeline Design
+2 more
5 answers I was asked this
+2
"High Level Architect Client v API Gateway v Object Storage v Message Queue v Worker v Database Client should can document with a web site or directly with API services. API Gateway should be used for upload document,get document info and state. Object storage should be used for original document and send event to Message Queue for starting. Message Queue is neccessary because there are millions of document should be process each time. Worker can get text from document with OCR. Database shoul"
Berk C. - "High Level Architect Client v API Gateway v Object Storage v Message Queue v Worker v Database Client should can document with a web site or directly with API services. API Gateway should be used for upload document,get document info and state. Object storage should be used for original document and send event to Message Queue for starting. Message Queue is neccessary because there are millions of document should be process each time. Worker can get text from document with OCR. Database shoul"See full answer
Software Engineer
Data Pipeline Design
+2 more
Asked at Databricks • a year ago
What's the difference between a data lakehouse and a data warehouse?
Data Engineer
Data Pipeline Design
5 answers I was asked this
+2
"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"
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
Data Engineer
Data Pipeline Design
Design an ETL Pipeline for a ML Platform for AWS
Data Engineer
Data Pipeline Design
Add answer I was asked this
Data Engineer
Data Pipeline Design
Design Netflix's Clickstream Data Pipeline
Business Analyst
Data Pipeline Design
+1 more
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Business Analyst
Data Pipeline Design
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Asked at Databricks • a year ago
How would you handle slow query performance for a single-user SQL endpoint in Databricks, where all sequentially run queries are affected?
Data Engineer
Data Pipeline Design
Add answer I was asked this
Data Engineer
Data Pipeline Design

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Asked at Google • a year ago
When is Hadoop better than PySpark?
Data Engineer
Data Pipeline Design
1 answer I was asked this
"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"
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
Data Engineer
Data Pipeline Design
Design an ETL Pipeline for Slack for School
Data Engineer
Data Pipeline Design
Add answer I was asked this
Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
How would you handle scheduling dependencies between two nightly Jobs to ensure the second Job does not fail if the first Job runs longer than expected?
Data Engineer
Data Pipeline Design
1 answer I was asked this
"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."
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
Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
What is a Medallion Architecture?
Data Engineer
Data Pipeline Design
1 answer I was asked this
Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
How would you handle a task in a nightly job that fails unexpectedly during 10 percent of the runs?
Data Engineer
Data Pipeline Design
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Data Engineer
Data Pipeline Design
Asked at Amazon • 2 years ago
Design a data pipeline that updates hourly and powers a dashboard showing the most common Alexa user requests, broken down by country.
Data Engineer
Data Pipeline Design
Add answer I was asked this
Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
What is delta lake?
Data Engineer
Data Pipeline Design
1 answer I was asked this
"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."
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
Data Engineer
Data Pipeline Design
Design a system to ingest large amounts of JSON data from multiple S3 buckets
Data Engineer
Data Pipeline Design
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Data Engineer
Data Pipeline Design
Design a data pipeline that complies with GDPR.
Data Engineer
Data Pipeline Design
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Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
When should you use a job cluster instead of an all-purpose cluster?
Data Engineer
Data Pipeline Design
1 answer I was asked this
"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"
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
Data Engineer
Data Pipeline Design
Asked at Databricks • a year ago
When should you use Delta Live Tables over standard data pipelines built on Spark and Delta Lake?
Data Engineer
Data Pipeline Design
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Data Engineer
Data Pipeline Design

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Data Pipeline Design Interview Questions

Design a document processing pipeline.

What's the difference between a data lakehouse and a data warehouse?

Design an ETL Pipeline for a ML Platform for AWS

Design Netflix's Clickstream Data Pipeline

How would you handle slow query performance for a single-user SQL endpoint in Databricks, where all sequentially run queries are affected?

When is Hadoop better than PySpark?

Design an ETL Pipeline for Slack for School

How would you handle scheduling dependencies between two nightly Jobs to ensure the second Job does not fail if the first Job runs longer than expected?

What is a Medallion Architecture?

How would you handle a task in a nightly job that fails unexpectedly during 10 percent of the runs?

Design a data pipeline that updates hourly and powers a dashboard showing the most common Alexa user requests, broken down by country.

What is delta lake?

Design a system to ingest large amounts of JSON data from multiple S3 buckets

Design a data pipeline that complies with GDPR.

When should you use a job cluster instead of an all-purpose cluster?

When should you use Delta Live Tables over standard data pipelines built on Spark and Delta Lake?

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