OEWS is a program of the U.S. Department of Labor, Bureau of Labor Statistics (BLS). This federal-state cooperative program produces employment and wage estimates annually for about 867 occupations. Each year, the Employment Security Department's Data Architecture, Transformation and Analytics (DATA) Division compiles occupational employment and wage estimates for Washington state. These data are presented statewide, for metropolitan statistical areas (MSAs) and nonmetropolitan areas (NMAs). All data are at the cross-industry level.
For more information, data and maps at the national level, see the BLS map tool, the 2018 standard occupational classification (SOC) codes, and the BLS glossary of terms.
Occupational employment and wage estimates for 2024
The 2024 OWES are available Excel format and in the dashboard below. Additional reports are available for download in the report library.
The source of the occupation and wage estimates and technical notes
The occupational employment and wage estimates are based on the spring 2023 Occupational Employment Statistics survey. Data from the spring 2023 survey are combined with the fall 2020, spring and fall 2021 and spring and fall 2022 survey panels.
The estimates in this publication are based on the 2010 Office of Management and Budget (OMB) area definitions, the 2022 North American Industry Classification System (NAICS) codes at the four-digit level and the full 2018 Standard Occupational Classification (SOC) code manual. Occupation and wage estimates are not provided for farms, the self-employed, owner/partners in unincorporated firms, the military, household workers or unpaid family workers. Estimates for some occupations or wage levels may be suppressed because they do not meet BLS publication standards or due to small sample size. These include occupations with an estimated employment of fewer than 10 people. Dashes shown in the data columns indicate suppressed data. Annual wages have been calculated by multiplying the hourly mean wage by 2080 hours. The relative standard error (RSE) is a measure of the reliability of a survey statistic. The smaller the relative standard error, the more precise the estimate.
How can I use this information?
- To set wages for employees.
- To compare wages regionally.
- To compare wages by occupation.
- For career planning.