Want to hire Data Factory developer? Then you should know!
How and where is Data Factory used?
- Real-time Data Processing: Monitoring sensor data
- Big Data Analytics: Analyzing customer behavior
- Data Warehousing: Storing historical data
- Data Migration: Moving data to the cloud
- Data Transformation: Converting file formats
Compare Junior, Middle, Senior, and Expert/Team Lead Data Factory Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 0-2 years |
| $60,000 |
Middle | 3-5 years |
| $80,000 |
Senior | 6-8 years |
| $100,000 |
Expert/Team Lead | 9+ years |
| $120,000 |
Quick Facts about Data Factory.
- Created in 2015 by Microsoft as a cloud-based data integration service.
- Most popularly used for ETL (Extract, Transform, Load) and data warehousing projects.
- Entry threshold requires basic knowledge of SQL and data integration concepts.
- Azure Data Factory is often used alongside Azure Databricks for big data processing.
- Fun Fact: The largest data pipeline ever built using Data Factory processed over 30 petabytes of data!
TOP Data Factory Related Technologies
- Azure Data Factory
- Python (Ex: Guido, 1991)
- Snowflake
- Apache Spark (Ex: Matei, 2009)
- Databricks
What are top Data Factory instruments and tools?
- Azure Data Factory: Microsoft’s data integration service
- Talend Data Fabric: Data integration and integrity tool
- Informatica PowerCenter: ETL tool by Informatica
- Matillion ETL: Cloud-native ETL tool
- Apache Nifi: Data automation tool by Apache
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager