Matillion Interview Questions

 1.What is Matillion?

Answer: Matillion is a cloud-native ETL/ELT platform designed specifically for cloud data warehouses like Snowflake, Redshift, and BigQuery. It provides a visual interface to design and run data pipelines.

2. What’s the difference between ETL and ELT?

Answer:

• ETL: Extract → Transform → Load (transformation happens before loading)
• ELT: Extract → Load → Transform (Matillion uses this; transformations happen in the warehouse)

3. Which cloud platforms does Matillion support?

Answer: Matillion supports AWS, Microsoft Azure, and Google Cloud through marketplace deployments or Matillion SaaS.

4. What data warehouses are compatible with Matillion?

Answer:

• Snowflake
• Amazon Redshift
• Google BigQuery
• Azure Synapse (via Matillion ETL for Data Productivity Cloud)

5. What are the two main types of jobs in Matillion?

Answer:

• Orchestration Jobs – handle external data movement and workflow control
• Transformation Jobs – execute data manipulation within the data warehouse

6. What is a component in Matillion?

Answer: A component is a building block in a job (e.g., S3 Load, SQL Script, Join, Filter) that performs specific ETL tasks.

7. How do you connect Matillion to a Snowflake database?

Answer: Provide account details (account URL, warehouse, database, schema), user credentials, and test the connection via environment variables.

8.What is a variable in Matillion?

Answer: Variables are dynamic placeholders used to pass values across jobs (e.g., table names, filters). They can be job-specific or global.

Intermediate Matillion Interview Questions

9.What is the role of Orchestration Jobs?

Answer: Orchestration jobs are used to:

• Load data from external sources (APIs, S3, FTP, etc.)
• Run transformation jobs
• Trigger events
• Schedule pipeline execution

10. What is the role of Transformation Jobs?

Answer: Transformation jobs apply logic (joins, filters, aggregations) to the data already loaded into the cloud data warehouse.

11.How do you load data from Amazon S3 using Matillion?

Use the “S3 Load” component in an orchestration job to load data from an S3 bucket into a staging table in your data warehouse.

12. What is the API Query Component in Matillion?

Answer:

A component that allows users to connect to REST APIs, extract data (usually JSON), and load it into a table using flattening.

13. How does Matillion handle error logging?

Answer:

Matillion provides task-level logging. Failed components highlight error messages and provide detailed logs in the “Tasks” panel.

14. How do you schedule jobs in Matillion?

Answer:

Use the built-in Scheduler to trigger jobs on a recurring basis (daily, hourly, etc.) or trigger jobs using webhooks or API calls.

15. What are shared jobs in Matillion?

Answer: Shared jobs are reusable job modules that can be called from multiple other jobs, useful for creating reusable logic blocks.

16. How do you flatten nested JSON in Matillion?

Use the “Flatten” component after extracting JSON via an API query. Specify the array/object path to normalize data into rows.

17. How do you use variables in a SQL Script Component?

sql

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SELECT * FROM ${schema}.${table_name} WHERE created_date > ‘${start_date}’

18. Can Matillion integrate with Git?

Answer: Yes, Matillion provides Git integration for version control and collaboration.

Also Read: Matillion Tutorial 

Advanced Matillion Interview Questions

19. How does Matillion perform transformations?

Answer: Matillion uses pushdown ELT: transformation logic is compiled into SQL and executed directly in the cloud data warehouse.

Explain the difference between Table Input and SQL Script components.

• Table Input: Drag-and-drop UI to select tables/columns
• SQL Script: Manually write SQL for more complex logic

What are grid variables?

Answer: Grid variables are tabular sets of variable values, useful for looping or passing multiple parameters to a job.

What is the Rewrite Table component?

Answer: It creates or replaces a table structure with a specified schema. Often used at the beginning of a transformation job.

How do you handle incremental loads in Matillion?

• Track last load timestamp
• Use a variable to store/update the value
• Apply a WHERE clause in data extraction components

How does Matillion ensure scalability?

• Built on cloud-native architecture
• Executes workloads within data warehouse
• Integrates with scalable storage/services (S3, Blob, GCS)

How can Matillion integrate with third-party tools?

Answer: Via:

• REST API components
• Python Script components
• Webhooks
• Matillion API and shared jobs

What is the difference between Matillion ETL and Matillion Data Loader?

• Matillion ETL: Self-hosted, full control over orchestration/transformation
• Matillion Data Loader: SaaS tool focused on ingestion pipelines (simplified UI)

Scenario-Based Matillion Interview Questions

How would you build a pipeline to ingest daily CSV files from S3 into Snowflake?

• Use S3 Load in orchestration job
• Load to staging table
• Call transformation job for cleaning & merging
• Use variable for dynamic file names
• Schedule job for daily execution

Your transformation job fails randomly. How do you debug it?

• Check component logs
• Review variable values
• Test queries in database console
• Use breakpoints and step-by-step execution

How would you implement data quality checks in Matillion?

• Use components like Row Count, Filter, Assert
• Add email notifications for failures
• Log invalid records separately

How can you automate deployment of Matillion jobs across environments (dev/stage/prod)?

• Use environment variables for schema/table differences
• Export/import jobs via JSON
• Use Git and CI/CD scripts for automation

SQL-Based Matillion Questions

Write a SQL to delete duplicate rows in a table.

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DELETE FROM sales_data WHERE id NOT IN ( SELECT MIN(id) FROM sales_data GROUP BY customer_id, order_date );

How to merge incremental data in transformation jobs?

• Load delta data
• Use Table Input + Join to compare with main table
• Apply Update/Delete + Insert logic based on keys

Matillion Best Practices (Common Interview Topic)

• Separate orchestration and transformation logic
• Parameterize everything with variables
• Use shared jobs for reusability
• Limit data volume in transformation jobs (push filtering early)
• Schedule jobs with dependencies properly
• Test pipelines with sample data before full runs
• Document jobs with annotations and naming conventions

Matillion Certification Questions (Quick Recap)

• What are orchestration components?
• How does Matillion implement ELT?
• Name 3 transformation components
• How do you pass values between jobs?
• What’s the use of Python Scripts in Matillion?

Conclusion

Matillion has become a cornerstone tool for modern data engineering in the cloud. This comprehensive list of Matillion interview questions will prepare you to ace interviews for roles involving cloud ETL/ELT, Snowflake, BigQuery, Redshift, and API integrations