Survey Data Processor information
See Texas salary details
$11.42 - $13.34
8% of jobs
$15.06 is the 25th percentile. Wages below this are outliers.
$13.34 - $15.25
19% of jobs
$15.25 - $17.16
17% of jobs
The median wage is $17.75 / hr.
$17.16 - $19.08
19% of jobs
$20.45 is the 75th percentile. Wages above this are outliers.
$19.08 - $20.99
16% of jobs
$20.99 - $22.90
13% of jobs
$22.90 - $24.82
4% of jobs
$24.82 - $26.73
2% of jobs
$26.73 - $28.65
0% of jobs
$28.65 - $30.56
0% of jobs
$30.56 - $32.47
1% of jobs
How much do survey data processor jobs pay per hour?
As of Sep 5, 2026, the average hourly pay for survey data processor in Texas is $18.88, according to ZipRecruiter salary data. Most workers in this role earn between $15.00 and $20.82 per hour, depending on experience, location, and employer.
A Survey Data Processor is responsible for collecting, organizing, and analyzing data gathered from surveys. They ensure the accuracy and integrity of survey results by cleaning and validating the data, coding responses, and using specialized software to process the information. Their work helps organizations interpret survey findings to make informed decisions and develop strategies. Survey Data Processors often collaborate with researchers, statisticians, and project managers to deliver clear and actionable reports.
To thrive as a Survey Data Processor, you need strong analytical skills, attention to detail, and proficiency in data entry and management, typically supported by a degree in statistics, mathematics, or a related field. Familiarity with statistical software such as SPSS, SAS, or Excel, and sometimes experience with survey platforms, is commonly required. Excellent organizational skills, time management, and the ability to communicate findings clearly are valuable soft skills in this role. These competencies ensure the accurate and efficient processing of survey data, supporting reliable research outcomes and informed decision-making.
Survey Data Processors often encounter challenges such as managing large volumes of data, ensuring data accuracy, and meeting tight deadlines. Handling inconsistencies or incomplete responses in survey results requires attention to detail and effective use of data cleaning tools. Collaboration with survey designers and analysts is essential to clarify ambiguous data points and ensure the final datasets are reliable. Staying organized and continuously updating one's proficiency with data processing software can help address these challenges efficiently.
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