CLOUD DATA LLC salaries
Median $94,000 across 27 filings for IT roles, Jul 2023 to Jun 2026.
Calculate take-home pay on the calculator pageMedian
$94,000
Middle 50%
$84,700–$103,300
Filings
27
- Median is 27% below the median for all IT roles ($128,000).
- Most filings are wage Level I (56%).
- Software Developers has the most filings (16), with a median of $97,600.
Based on 27 filings. Small samples can differ from actual pay ranges.
Salaries by role
| Role | Filings | Median |
|---|---|---|
| Software Developers | 16 | $97,600 |
| Data Scientists | 5 | $94,000 |
| Computer Systems Analysts | 3 | $88,000 |
| Computer Occupations, All Other | 2 | $83,900 |
| Network and Computer Systems Administrators | 1 | $77,500 |
Top metros
| Metro | Filings | Median |
|---|---|---|
| New York-Newark-Jersey City, NY-NJ | 6 | $99,700 |
| Dallas-Fort Worth-Arlington, TX | 4 | $87,500 |
| San Jose-Sunnyvale-Santa Clara, CA | 3 | $146,300 |
| Austin-Round Rock-San Marcos, TX | 2 | $97,100 |
| Orlando-Kissimmee-Sanford, FL | 2 | $97,100 |
| Winston-Salem, NC | 2 | $85,500 |
| Allentown-Bethlehem-Easton, PA-NJ | 1 | $89,600 |
| Atlanta-Sandy Springs-Roswell, GA | 1 | $94,000 |
| Boston-Cambridge-Newton, MA-NH | 1 | $77,500 |
| Chicago-Naperville-Elgin, IL-IN | 1 | $85,500 |
Level I 56%
Level II 41%
Level III 4%
Take-home pay
| Gross | $94,000 |
| Federal income tax | $11,900 |
| Social Security | $5,800 |
| Medicare | $1,400 |
| State income tax | $4,500 |
| Health insurance (employee share) | $1,400 |
| Take-home per year | $69,000 |
| Take-home per month | $5,800 |
Tax year 2026, single filer.
Local taxes, 401(k), and filing status other than single are not included.
Tax rates checked against IRS, Tax Foundation, and other original sources on Oct 28, 2026.
This is an estimate. Actual taxes depend on your situation. Consult a tax professional before filing.
LCA filings are not hires.
Filed wages are offered base pay, not total compensation.
We did not independently verify the source files. Deduplication and filtering can cause differences from the original data.