Want to hire Data QA developer? Then you should know!
How and where is Data QA used?
- Data Cleaning: Removing duplicate records
- Data Validation: Ensuring data accuracy
- Data Transformation: Converting data formats
- Data Integration: Combining different data sources
- Data Profiling: Analyzing data quality
- Data Monitoring: Tracking data changes
- Data Masking: Protecting sensitive information
- Data Anonymization: Safeguarding privacy
- Data Migration: Moving data to new systems
- Data Archiving: Storing data for long-term retention
Compare Junior, Middle, Senior, and Expert/Team Lead Data QA Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 0-2 years | Responsibilities & Activities:
| $50,000 |
Middle | 2-5 years | Responsibilities & Activities:
| $70,000 |
Senior | 5-8 years | Responsibilities & Activities:
| $90,000 |
Expert/Team Lead | 8+ years | Responsibilities & Activities:
| $120,000 |
Quick Facts about Data QA.
- When Data QA Software Development was born: 53 chars
- The top project types that utilize this tech: 62 chars
- The minimum skill level required to get started: 64 chars
- The most popular companion technology in this field: 58 chars
- A fascinating trivia about Data QA Software Development: 83 chars
TOP Data QA Related Technologies
- DataRobot (Jeremy, 2012)
- Tricentis Tosca (Sebastian, 2007)
- Selenium (Jason, 2004)
- TestComplete (Alex, 1999)
- Apache JMeter (Stefan, 1998)
What are top Data QA instruments and tools?
- GreatExpectations: Automated data quality testing released by Superconductive in 2018
- Informatica Data Quality: Comprehensive data quality tool by Informatica since 2002
- Talend Data Quality: Open-source data quality tool by Talend released in 2006
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