All 132 questions
What is the difference between ETL and ELT, and when would you use each in data pipeline development?
Asked in 6 of 307 interviews · last asked Oct 19 · Concept · Mid-level
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ETL means extract, transform, load: data is changed before it reaches the target system. ELT means extract, load, transform: data is loaded first and changed inside the target system. Use ETL when data must be cleaned or masked before loading, or the target has limited processing power. Use ELT when the target can handle transformations efficiently.
- ETL uses a separate processing step before loading; ELT uses the target system for transformations.
- ETL can keep sensitive raw data out of the target.
- ELT can retain raw data for later changes, but needs access controls and enough computing power.
What the interviewer checks: The interviewer is checking whether you understand the processing order and can choose based on privacy and system capabilities.
Other ways it was asked
- “What is the difference between ETL and ELT?”
- “What are ETL and ELT, and how do they differ?”
How do you develop and maintain data pipelines, including ETL processes?
Asked in 5 of 307 interviews · last asked Oct 22 · Scenario · Mid-level
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I define the source data, target tables, and freshness needs, then build extraction, transformation, and loading steps. I use SQL or Python for processing and a scheduler such as Airflow to manage runs. I add data checks, safe retries, and alerts, then maintain the pipeline through monitoring, tests, version control, and updates when source data changes.
- Check required fields, duplicates, row counts, and business rules.
- Make reruns safe so retries do not duplicate or corrupt data.
- Track failures, data freshness, and runtime; alert the team when limits are missed.
- Test source schema changes and keep a way to reload missing or incorrect data.
What the interviewer checks: The interviewer checks whether you can build the full pipeline and keep its data correct and reliable over time.
Other ways it was asked
- “How do you work on data pipelines?”
- “How do you process data in an ETL pipeline, from extraction through transformation and loading?”
- “How do you build an ETL pipeline?”
What is the difference between batch processing and stream processing?
Asked in 4 of 307 interviews · last asked Oct 19 · Concept · Mid-level
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Batch processing handles a finite set of data in one run. Stream processing handles incoming data continuously, usually with lower delay. I use batch for scheduled reports and large historical loads, and streaming for alerts or dashboards that need fresh data quickly.
- Batch is often simpler to operate when results do not need to be immediate.
- Streaming must account for late events, duplicate records, and failures.
- Spark uses spark.read for batch data and spark.readStream for streaming data; Structured Streaming usually uses micro-batches.
What the interviewer checks: The interviewer checks whether you can choose an approach based on data arrival, acceptable delay, and operational complexity.
Other ways it was asked
- “What are stream processing and batch processing, and when would you use each?”
- “What is the difference between batch processing and streaming?”
- “What is the difference between batch and stream processing, and how do you read data with Spark?”
What is the medallion architecture for data processing?
Asked in 3 of 307 interviews · last asked Oct 24 · Concept · Mid-level
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Medallion architecture organizes data into three layers: bronze, silver, and gold. Bronze keeps raw data from source systems. Silver cleans, checks, and combines that data. Gold holds business-ready data, often summarized for reports and analysis.
- Data quality and structure improve as data moves through the layers.
- Keeping raw data lets teams reprocess it when rules change or errors occur.
- Layers are logical stages; they do not require separate storage systems.
What the interviewer checks: The interviewer checks whether you know each layer’s role and how the layers turn raw data into trusted business data.
Other ways it was asked
- “What is medallion architecture, and how does it work?”
- “What is a medallion architecture, and how do its layers organize data?”
What is ETL?
Asked in 3 of 307 interviews · last asked Aug 9 · Concept · Junior
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ETL stands for Extract, Transform, Load. It takes data from source systems, cleans or reshapes it, and loads it into a target such as a data warehouse. It supports data ingestion by bringing source data into a consistent form for reporting and analysis.
- Extract reads data from sources such as databases, files, or APIs.
- Transform cleans, validates, and reshapes the data.
- Load writes the transformed data into the target system.
What the interviewer checks: The interviewer is checking whether you understand the three steps and how they move data from sources to a usable target.
Other ways it was asked
- “What is ETL, and how does it support data ingestion?”
What is data engineering?
Asked in 3 of 307 interviews · last asked Sep 14 · Concept · Junior
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Data engineering is building and running systems that collect, store, and prepare data for use. Data engineers create pipelines that move data from source systems, clean it, and make it ready for reports, analysis, or machine learning. They keep data reliable, secure, and available when needed.
- Build pipelines to collect, transform, and deliver data.
- Manage data storage, data quality, and access.
- Monitor pipelines and fix failures so data stays available.
What the interviewer checks: The interviewer is checking whether you understand how data engineering makes data usable and reliable for others.
Other ways it was asked
- “What is data science engineering?”
Tell me about a time you designed an end-to-end ETL pipeline, from extraction through data delivery, integrating multiple data sources while ensuring data quality.
Asked in 2 of 307 interviews · last asked Sep 20 · Behavioral · Senior
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I designed a daily sales pipeline combining database orders, API payments, and CSV refunds. I stored incremental extracts in raw storage, then cleaned, deduplicated, and joined them in a warehouse. I checked required fields, unique keys, and source totals before publishing tables for dashboards. An orchestrator managed dependencies, safe retries, and alerts; failed checks blocked publication.
- Explain how each source was extracted and how changes were tracked.
- Describe how you matched records across sources and handled missing or duplicate data.
- Show how quality checks controlled publication to downstream users.
- Explain how reruns avoided duplicates and how failures were detected and recovered.
What the interviewer checks: The interviewer is checking whether you owned the full pipeline and can explain its design, reliability, and data quality.
Other ways it was asked
- “Can you give a detailed end-to-end example of a data pipeline you built, including how you ingested and transformed data, delivered it to downstream users, and ensured data quality?”
How would you design a data ingest and transformation pipeline for a retail company using Azure Data Factory and Azure Databricks to process data from multiple sources and load the results into a Delta Lake, maximizing performance and handling failures effectively?
Asked in 2 of 307 interviews · last asked Aug 11 · Design · Senior
Show answer
I would use Azure Data Factory to ingest incremental data from each source into raw storage on ADLS. Databricks would clean, join, and aggregate it into Delta tables with bronze, silver, and gold layers. I would tune ingestion parallelism, Spark joins, and file sizes for speed. Retries, monitoring, and safe reruns would handle failures.
- Track CDC positions or watermarks per source; advance them only after successful processing.
- Deduplicate records before Delta MERGE and use stable keys so batch reruns do not create duplicates.
- Use autoscaling job compute, avoid small files, and partition large tables only where queries benefit.
- Set bounded retries, quarantine bad records, and alert on failures; use managed identities and Key Vault.
What the interviewer checks: The interviewer checks whether you can connect ingestion, transformation, performance, cost, security, and reliable recovery in one design.
Other ways it was asked
- “You're tasked with designing an ETL pipeline using Azure Databricks to process incremental data loads from Azure Data Lake. The data contains multiple large Parquet files, and you need to perform transformations such as filtering, aggregations, and data enrichment before writing the output back to Azure SQL database. How would you ensure efficient data processing, optimize costs, and handle potential failures in the pipeline?”
- “How would you structure an Azure Data Factory pipeline to optimize performance and ensure fault tolerance when ingesting large volumes of data from multiple sources, transforming it, and loading it into Azure SQL Database?”
- “How would you design an Azure Data Factory pipeline for data ingestion from on-premise SQL Server, processing in Azure Databricks, and loading into Azure Synapse Analytics to ensure security, scalability, and performance?”
What are the key challenges you typically encounter when building data integration pipelines?
Asked once · last asked May 19 · Scenario · Senior
Other ways it was asked
- “What other challenges can arise when building data integration pipelines?”
Would you pass each event through the normalizer individually or process events in batches?
Asked once · last asked Jul 20 · Design · Mid-level
How would you design the tools and data pipeline for an AI scorecard agent?
Asked once · last asked Jul 25 · Design · Senior
How would you design an ETL process to move retail data from source to target?
Asked once · last asked Sep 16 · Scenario · Mid-level
What is your approach to providing an end-to-end data warehouse solution for a client?
Asked once · last asked Sep 19 · Design · Mid-level
Other ways it was asked
- “What would be your approach to implementing a data warehouse from scratch and delivering an end-to-end solution?”
How would you create a healthcare data warehouse?
Asked once · last asked Sep 19 · Design · Mid-level
Other ways it was asked
- “How would you create a healthcare data warehouse for a client?”
- “How do you create a data warehouse?”
Where should business logic be applied in a file-ingestion pipeline that loads data into multiple database tables?
Asked once · last asked Oct 7 · Design · Senior
How would you design an end-to-end Apache NiFi flow to process a 4-GB file?
Asked once · last asked Feb 6 · Tooling · Mid-level
How would you integrate Power BI with an ERP system, designing the connection and data flows end to end and evaluating the outcome?
Asked once · last asked Feb 10 · Behavioral · Senior
Other ways it was asked
- “Tell me about a project where you integrated Power BI with an ERP system. How did you design the connection and data flows, and what was the outcome?”
What source types and data models, such as fact, dimension, and event tables, are commonly used in data pipelines?
Asked once · last asked Mar 3 · Concept · Mid-level
How do you build resiliency into data solutions, and what techniques do you use?
Asked once · last asked Mar 3 · Scenario · Senior
Can you explain the data analytics process, including how data is collected and analyzed?
Asked once · last asked Mar 28 · Concept · Junior
How would you approach implementing an AI workflow or ETL process in the cloud, and how would you address the main challenges?
Asked once · last asked Apr 17 · Behavioral · Mid-level
Other ways it was asked
- “Could you describe a specific project in which you implemented an AI workflow or ETL process in the cloud, including the challenge and how you approached it?”
How would you design a data architecture, pipeline, AI system, or knowledge platform, explaining the use case and main architectural components?
Asked once · last asked Apr 20 · Design · Senior
Other ways it was asked
- “Describe a data architecture, pipeline, AI system, or knowledge platform you helped design. What was the use case, what role did you play, and what were the architecture's main components?”
How would you explain ETL and complex ETL data-transformation logic to nontechnical stakeholders?
Asked once · last asked May 3 · Scenario · Mid-level
How would you build dataset versioning and lineage so you can reproduce any model run using its data, labels, features, and code, and roll back safely?
Asked once · last asked May 5 · Design · Senior
What is the medallion architecture, and why is it preferred over a traditional flat data lake?
Asked once · last asked May 9 · Concept · Mid-level
Could you describe the typical stages of a simple batch ETL pipeline that loads data from a relational database into a data warehouse table? What happens in the extract, transform, and load phases?
Asked once · last asked May 18 · Concept · Junior
How is a data pipeline architected, from data ingestion through transformation, and which tools are used at each stage?
Asked once · last asked May 27 · Design · Mid-level
What are the key features of a robust ETL pipeline?
Asked once · last asked May 27 · Concept · Mid-level
How would you design a high-capacity data pipeline and address its technical challenges?
Asked once · last asked Jun 3 · Design · Senior
Other ways it was asked
- “Describe a high-capacity data pipeline you built, including its design and the challenges you addressed.”
What kinds of requirements would you capture for a data pipeline?
Asked once · last asked Jun 9 · Scenario · Mid-level
How would you design an end-to-end RAG pipeline, including its data sources and architectural or machine-learning choices?
Asked once · last asked Jun 12 · Design · Senior
When would you virtualize on-premises Oracle data with a tool such as Denodo, and when would you physically ingest it into a lakehouse?
Asked once · last asked Jun 16 · Design · Senior
What criteria would lead you to replicate data rather than consume it directly from the source?
Asked once · last asked Jun 16 · Scenario · Senior
Tell me about a time you designed a system, introduced a new solution, or migrated an application to a data platform.
Asked once · last asked Jun 22 · Behavioral · Senior
How would you collaborate with analysts or data scientists to gather requirements and ensure you deliver the data products or structures they need?
Asked once · last asked Jun 24 · Behavioral · Mid-level
Other ways it was asked
- “What experience do you have collaborating with analysts or data scientists? How did you gather their requirements and ensure you delivered the data products or structures they needed?”
How would you manage data pipelines for model outputs or feature stores in an AI-powered service?
Asked once · last asked Jun 24 · Design · Senior
How do you decide between real-time, batch, and other data-ingestion patterns for a use case?
Asked once · last asked Jul 16 · Scenario · Mid-level
How would you take a four-source marketing data architecture from design through end-to-end implementation?
Asked once · last asked Jul 31 · Design · Senior
What is micro-batch processing, and when would you use it?
Asked once · last asked Aug 11 · Concept · Mid-level
How would you design an ingestion layer that accepts data from various client devices, stores it safely, and treats redaction as a black box? What infrastructure tools would you use?
Asked once · last asked Aug 11 · Design · Senior
How do you build ETL or ELT pipelines in Databricks, and which orchestration tools have you used?
Asked once · last asked Aug 12 · Tooling · Mid-level
How does a record change as it moves through the three layers of the medallion architecture?
Asked once · last asked Aug 20 · Concept · Mid-level
Other ways it was asked
- “What changes to a record as it moves through the three layers of the medallion architecture?”
How do Hadoop and Spark SQL fit into an ETL workflow?
Asked once · last asked Aug 20 · Concept · Mid-level
Where does the Hadoop ecosystem fit in a data engineering architecture?
Asked once · last asked Aug 25 · Concept · Mid-level
What are the key data-processing stages and business requirements in an insurance claims pipeline?
Asked once · last asked Aug 25 · Case · Mid-level
What operations and transformations are typically performed when moving data from the Bronze layer to Silver and then to Gold?
Asked once · last asked Aug 25 · Concept · Mid-level
How would you design an AI integration and an API processing architecture for one million incoming records?
Asked once · last asked Aug 25 · Design · Senior
What are common sink options for a data pipeline, and how do you choose where to store processed data?
Asked once · last asked Aug 25 · Design · Junior
What are the architectural trade-offs of using Snowflake dynamic tables versus a traditional combination of streams and tasks?
Asked once · last asked Aug 26 · Design · Senior
Other ways it was asked
- “What are the architectural trade offs of using dynamic tables versus a traditional combination of streams and tasks?”
How do you approach architecting an end-to-end data system when you inherit an architecture designed by another team or vendor?
Asked once · last asked Aug 26 · Scenario
How would you select a technology stack and build a data platform during its first 90 days?
Asked once · last asked Aug 26 · Scenario
How are consultants balancing traditional actuarial tools with newer programming languages or automated data pipelines like Python when building client models?
Asked once · last asked Aug 28 · Concept · Mid-level
Could you explain the architecture you would build when designing an ETL pipeline? What phases does the data pipeline go through?
Asked once · last asked Aug 29 · Design · Mid-level
What are the key stages of an ETL pipeline, and how do you decide their order?
Asked once · last asked Aug 29 · Design · Mid-level
If you were designing a data pipeline for a startup that is rapidly evolving, with budget constraints, how would you choose between a scalable cloud-based service and building a custom in-house solution?
Asked once · last asked Aug 31 · Design · Senior
Tell me about a data engineering project where you combined multiple data sources, transformed the data to meet business requirements, and optimized the pipeline.
Asked once · last asked Sep 1 · Behavioral · Mid-level
How would you design an Azure data pipeline for a daily 10 GB ingestion use case?
Asked once · last asked Sep 1 · Design · Mid-level
Given carte blanche, how would you approach designing a data pipeline system, starting simple?
Asked once · last asked Sep 2 · Design · Senior
What additional considerations would you account for when building a metrics ingestion and dashboarding flow?
Asked once · last asked Sep 2 · Design · Mid-level
Can you describe the end-to-end data flow in a regulatory reporting system?
Asked once · last asked Sep 4 · Design · Senior
How would you create a 90-day plan to unify data across systems for fraud detection at an acquired bank?
Asked once · last asked Sep 4 · Case · Senior
How would you build a Microsoft Fabric pipeline to ingest, transform, and load data from three sources into one Lakehouse?
Asked once · last asked Sep 9 · Design · Mid-level
How would you use Microsoft Fabric to work with data from Fabric, Google Cloud Platform, and SQL sources, and optimize the solution?
Asked once · last asked Sep 9 · Design · Senior
A company needs batch and streaming processing, including hourly and real-time workloads, in GCP. Which technology would you choose?
Asked once · last asked Sep 9 · Design · Senior
Why might Pub/Sub alone not be sufficient for a GCP solution that needs both batch and streaming processing?
Asked once · last asked Sep 9 · Concept · Senior
Why might Dataproc not be the best choice for a GCP solution that needs both batch and streaming processing?
Asked once · last asked Sep 9 · Concept · Senior
How would you design an end-to-end data pipeline for 5 million customer records per day, including ingestion, transformation, storage, restoration, and visualization?
Asked once · last asked Sep 9 · Design · Senior
Other ways it was asked
- “How would you design an end-to-end data pipeline to ingest, transform, store, orchestrate, and visualize 5 million customer records per day?”
How would you design a system to handle a very large database of files and store their data in a vector database?
Asked once · last asked Sep 13 · Design · Mid-level
What are the key components a data platform needs to ingest batch, streaming, and diverse enterprise data sources?
Asked once · last asked Sep 14 · Design · Senior
Why use notebooks in Microsoft Fabric, and when would you use them with a data warehouse or OneLake?
Asked once · last asked Sep 16 · Concept · Mid-level
What are the drawbacks of storing all data in a single layer rather than separating it into Silver and Gold layers?
Asked once · last asked Sep 16 · Concept · Mid-level
What are the benefits of a layered data architecture compared with a single-layer approach?
Asked once · last asked Sep 16 · Concept · Mid-level
Which GCP services would you use to build a data pipeline, and why?
Asked once · last asked Sep 16 · Design · Mid-level
When would you use real-time APIs or event streams rather than batch-based data integration?
Asked once · last asked Sep 16 · Concept · Mid-level
How do open table formats enable data to be accessed by multiple compute engines?
Asked once · last asked Sep 16 · Concept · Senior
What is the difference between Dataflow and Dataproc?
Asked once · last asked Sep 17 · Concept · Mid-level
What are Parquet and Avro, and how does data orchestration differ from data file formats?
Asked once · last asked Sep 17 · Concept · Mid-level
What parts of a data synchronization process would you make asynchronous, and how would you implement them?
Asked once · last asked Sep 18 · Scenario · Senior
What are the bronze, silver, and gold layers?
Asked once · last asked Sep 19 · Concept · Junior
How would you design the data flow behind a Power BI solution while keeping reporting logic out of the dashboard where possible?
Asked once · last asked Sep 20 · Design · Senior
Other ways it was asked
- “Walk me through the data flow behind a Power BI solution you delivered, and how you kept reporting logic out of the dashboard where possible.”
Design a batch pipeline that sends customer and transaction data to a financial crime monitoring platform. Walk through ingestion, validation, publication, failure recovery, and evidence.
Asked once · last asked Sep 20 · Design · Senior
What is the difference between Apache Airflow and Kafka?
Asked once · last asked Sep 20 · Concept · Mid-level
Tell me about a data engineering project you delivered, from the original business problem through the pipeline, data model, and validation. What parts were you personally responsible for?
Asked once · last asked Sep 21 · Behavioral · Mid-level
Walk me through a data engineering project from the business problem through ingestion, transformation, data modeling, and validation.
Asked once · last asked Sep 22 · Behavioral · Mid-level
How would an end-to-end machine-learning pipeline collect data from a website and use it for training?
Asked once · last asked Sep 22 · Design · Mid-level
For a table with billions of rows, would you choose ETL or ELT?
Asked once · last asked Sep 22 · Scenario · Senior
How would you explain an end-to-end data pipeline, from an API call to data becoming available in Snowflake?
Asked once · last asked Sep 22 · Design · Senior
Can you describe an end-to-end data pipeline architecture, from ingestion to data consumption?
Asked once · last asked Sep 22 · Design · Mid-level
How would you build a GCP data pipeline from ingestion to the final BigQuery table?
Asked once · last asked Sep 23 · Tooling · Senior
Other ways it was asked
- “Can you walk me through one actual GCP pipeline from ingestion to the final BigQuery table, and what was your personal responsibility?”
Can you give an example of an end-to-end data solution you were responsible for delivering, and explain how you kept it moving through rollout and delivery?
Asked once · last asked Sep 23 · Behavioral · Mid-level
When delivering an end-to-end data solution, how do you decide whether to follow established organizational patterns or develop new ones?
Asked once · last asked Sep 23 · Scenario · Senior
How would you design the end-to-end architecture and data flow for a billing automation pipeline?
Asked once · last asked Sep 24 · Design · Mid-level
When would you use Dataproc alongside BigQuery if transformations and loading are handled in BigQuery?
Asked once · last asked Sep 24 · Concept · Mid-level
How would you set up an SAP Analytics Cloud model and data pipeline from SAP BW to analyze and plan sales data by product, brand, and country?
Asked once · last asked Sep 24 · Design · Senior
How would you design a data solution using Microsoft Fabric, including its components, integrations, and workflow?
Asked once · last asked Sep 24 · Design · Mid-level
Other ways it was asked
- “Can you describe a project where you used Microsoft Fabric, including the components, integrations, and workflow involved?”
How would you handle enterprise data architecture for millions of records across Salesforce and analytics needs?
Asked once · last asked Sep 30 · Design · Senior
How would you qualify, unify, load, and secure high-volume data for dashboards and reporting?
Asked once · last asked Sep 30 · Design · Senior
When building a reporting solution, how do you decide which logic belongs in the data warehouse or dbt and which should remain in Power BI?
Asked once · last asked Oct 1 · Design · Senior
If a stakeholder wants daily updates but the source delivers data weekly, how would you agree on a useful solution without creating false expectations?
Asked once · last asked Oct 1 · Scenario · Mid-level
In a layered data lake, what belongs in each layer, which layer should BI consume from, and should a new business rule be implemented in the pipeline or in DAX?
Asked once · last asked Oct 2 · Design · Senior
How would you design an Azure Data Factory pipeline for a food delivery analytics project?
Asked once · last asked Oct 7 · Design · Mid-level
How would you architect an application that ingests large CSV, TSV, or similar text files into AWS, processes them as soon as they land, applies business logic, and loads different database tables?
Asked once · last asked Oct 7 · Design · Senior
What are the trade-offs of reading and processing a file directly rather than using an event-driven pipeline?
Asked once · last asked Oct 7 · Scenario · Senior
Can you describe the lifecycle of a data project?
Asked once · last asked Oct 9 · Concept · Mid-level
How would you design a secure document intelligence workflow for sensitive financial documents, including time-bounded access, data extraction, and surfacing insights to business users?
Asked once · last asked Oct 12 · Design · Senior
How would you design a data pipeline for a telecommunications customer churn model?
Asked once · last asked Oct 18 · Design · Senior
What is Alteryx? Is it just another business visualization software?
Asked once · last asked Jan 13 · Concept · Junior
What are the bronze, silver, and gold layers in medallion architecture?
Asked once · last asked Oct 24 · Concept · Mid-level
How do you maintain fact and dimension tables?
Asked once · last asked Sep 19 · Scenario · Mid-level
Other ways it was asked
- “Can you give an example of how you maintain fact and dimension tables?”
What are the various steps involved in processing data?
Asked once · last asked Mar 5 · Concept · Junior
Where do APIs fit in an end-to-end cloud data pipeline?
Asked once · last asked Apr 30 · Concept · Mid-level
How would you divide and manage the data-processing pipeline across four domains?
Asked once · last asked May 18 · Design · Senior
What are data pipelines and data ingestion, and how are they used?
Asked once · last asked Jun 25 · Concept · Junior
What role does a load balancer play between a data pipeline and third-party platforms?
Asked once · last asked Jul 20 · Concept · Mid-level
How do you explain timestamp lineage in plain English to someone outside engineering?
Asked once · last asked Aug 17 · Concept · Mid-level
How do you get started with Hadoop?
Asked once · last asked Aug 19 · Tooling · Junior
What are ETL pipelines, and what tools are commonly used to build them?
Asked once · last asked Aug 20 · Concept · Junior
How do you use AI in your data engineering work?
Asked once · last asked Aug 26 · Scenario · Mid-level
What is the difference between big data and traditional data analysis?
Asked once · last asked Aug 27 · Concept · Junior
What type of technologies are used in big data?
Asked once · last asked Aug 27 · Concept · Junior
What is SSIS?
Asked once · last asked Aug 29 · Concept · Junior
What are Delta Live Tables in Databricks?
Asked once · last asked Sep 4 · Concept · Junior
What is the difference between a data engineer and a data analyst?
Asked once · last asked Sep 14 · Concept · Junior
What platforms or tools do you use when you build an ETL pipeline?
Asked once · last asked Sep 15 · Tooling · Junior
How do you use SQL in data engineering?
Asked once · last asked Sep 17 · Tooling · Mid-level
Why is Data Factory used in Microsoft Fabric?
Asked once · last asked Sep 18 · Concept · Junior
How would you handle patient medical-condition data in a healthcare data warehouse?
Asked once · last asked Sep 19 · Scenario · Mid-level
What is the difference between a data engineer and a data scientist?
Asked once · last asked Sep 21 · Concept · Junior
Can you tell me generally what Kimball principles and dbt are?
Asked once · last asked Sep 29 · Concept · Junior
In a layered data architecture, what purpose do the layers serve, and how would you implement them?
Asked once · last asked Oct 18 · Concept · Mid-level
What best practices do you follow when designing data engineering projects?
Asked once · last asked Oct 19 · Scenario · Mid-level
How would you choose tools for data processing and visualization, and automate data cleaning or reporting?
Asked once · last asked Oct 19 · Scenario · Junior
Other ways it was asked
- “What tools and technologies did you use for your data and visualization? Did you automate any part of the data cleaning or reporting process? And if so, how?”
More ETL and Data Pipelines interview questions
- All ETL and Data Pipelines interview questions
- Data Ingestion and Transformation Interview Questions
- Dbt Interview Questions
- Data Pipeline Orchestration and Deployment Interview Questions
- Incremental Loading, CDC, and Streaming Interview Questions
- ETL Data Quality and Validation Interview Questions
- Data Pipeline Performance Optimization Interview Questions
- Data Pipeline Monitoring and Troubleshooting Interview Questions
- Data Migration Interview Questions
How this list is made
Every question here was asked by a real interviewer in a real job interview that a candidate ran MeetAssist in. After the call, the interviewer's questions are pulled from the transcript. Practice sessions, tests, exams and anything that was not a job interview are dropped.
Questions are rewritten so they make sense on their own: names of people, employers and clients are removed, and speech-to-text mistakes are fixed. Small talk, logistics and questions about one candidate's own résumé are left out. Rephrasings of the same question are merged, and the count is the number of different interviews it came up in.
The interviews come from candidates who use MeetAssist, so they lean towards software, data and AI roles: the shares describe these interviews, not every ETL and Data Pipelines interview. Answers to the most asked questions are written and checked by an editor; a "common mistake" is shown only when reviews of real answers in these interviews show it, with the count.
307 interviews, 169 candidates, Nov 2025 to Oct 2026. Updated every month with new interviews.
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