Data Processing Engineer Salary in California
$43.9K - $55.8K
0% of jobs
$55.8K - $67.6K
1% of jobs
$67.6K - $79.4K
3% of jobs
$79.4K - $91.3K
5% of jobs
$91.3K - $103.1K
7% of jobs
$112.2K is the 25th percentile. Wages below this are outliers.
$103.1K - $115K
11% of jobs
$115K - $126.8K
11% of jobs
The median wage is $129.9K / yr.
$126.8K - $138.7K
44% of jobs
$138.7K - $150.5K
9% of jobs
$150.5K - $162.3K
6% of jobs
$162.3K - $174.2K
4% of jobs
$43.9K
$132.2K
$175.2K
$128,018
/year
$61.55
/hour
Data Processing Engineer Salary Comparison by Location
Nationwide
United States
$129,716
California
California
$128,018
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How much does a Data Processing Engineer make in California?
As of Aug 27, 2026, the average annual pay for a Data Processing Engineer in California is $128,018 a year.
Just in case you need a simple salary calculator, that works out to be approximately $61.55 an hour. This is the equivalent of $2,461/week or $10,668/month.
While ZipRecruiter is seeing salaries as high as $175,176 and as low as $43,917, the majority of Data Processing Engineer salaries currently range between $113,000 (25th percentile) to $135,700 (75th percentile) with top earners (90th percentile) making $159,878 annually in California. The average pay range for a Data Processing Engineer varies little (about 22700), which suggests that regardless of location, there are not many opportunities for increased pay or advancement, even with several years of experience.
California ranks number 50 out of 50 states nationwide for Data Processing Engineer salaries.
To estimate the most accurate annual salary range for Data Processing Engineer jobs, ZipRecruiter continuously scans its database of millions of active jobs published locally throughout America.
Find your next high paying job as a Data Processing Engineer on ZipRecruiter today.
What are Top 10 Highest Paying Cities for Data Processing Engineer Jobs in California
We've identified 10 cities where the typical salary for a Data Processing Engineer job is above the average in California in California. Topping the list is Cupertino, , with Mountain View, and San Francisco, close behind in the second and third positions. San Francisco, beats the average in California by $24,810 (19.4%), and Cupertino, furthers that trend with another $32,019 (25.0%) above the $128,018 average.
With these 10 cities paying on average above the average for California, the opportunities for economic advancement by changing locations as a Data Processing Engineer appears to be exceedingly fruitful.
Finally, another factor to consider is the average salary for these top 10 cities varies very little at 7% between Cupertino, and Oakland, , reinforcing the limited potential for much wage advancement. The possibility of a lower cost of living may be the best factor to use when considering location and salary for a Data Processing Engineer role.
City | Annual Salary | Hourly Wage |
|---|---|---|
Cupertino | $160,037 | $76.94 |
Mountain View | $153,024 | $73.57 |
San Francisco | $152,828 | $73.47 |
Palo Alto | $152,484 | $73.31 |
Santa Clara | $152,344 | $73.24 |
Sunnyvale | $152,242 | $73.19 |
San Jose | $151,992 | $73.07 |
Daly City | $150,302 | $72.26 |
Santa Cruz | $149,779 | $72.01 |
Oakland | $148,976 | $71.62 |
What are Top 5 Best Paying Related Data Processing Engineer Jobs in California
Analyzing similar jobs related to the Data Processing Engineer job category in California, we found 5 that were relevant. However, none pay more than the $128018 state average for Data Processing Engineer jobs.
Nevertheless Sr Data Engineer, Big Data Devops Engineer, or Big Data Analytics may still be interesting positions to explore.
Job Title | Annual Salary | Hourly Wage |
|---|---|---|
Sr Data Engineer | $124,674 | $59.94 |
Big Data Devops Engineer | $124,260 | $59.74 |
Big Data Analytics | $121,596 | $58.46 |
Etl Target | $117,783 | $56.63 |
Associate Programmer Analyst | $60,546 | $29.11 |
About Our Data
ZipRecruiter salary estimates, histograms, trends and comparisons are derived from both employer job postings and third party data sources.
