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Computer applications engineer vs data engineer

The differences between computer applications engineers and data engineers can be seen in a few details. Each job has different responsibilities and duties. It typically takes 2-4 years to become both a computer applications engineer and a data engineer. Additionally, a data engineer has an average salary of $109,675, which is higher than the $96,367 average annual salary of a computer applications engineer.

The top three skills for a computer applications engineer include FANUC, machine tools and CAD/CAM. The most important skills for a data engineer are python, java, and cloud.

Computer applications engineer vs data engineer overview

Computer Applications EngineerData Engineer
Yearly salary$96,367$109,675
Hourly rate$46.33$52.73
Growth rate21%21%
Number of jobs128,496303,105
Job satisfaction--
Most common degreeBachelor's Degree, 63%Bachelor's Degree, 65%
Average age3939
Years of experience44

Computer applications engineer vs data engineer salary

Computer applications engineers and data engineers have different pay scales, as shown below.

Computer Applications EngineerData Engineer
Average salary$96,367$109,675
Salary rangeBetween $71,000 And $129,000Between $80,000 And $149,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaCalifornia
Best paying companyCheggThe Citadel
Best paying industryTechnologyTechnology

Differences between computer applications engineer and data engineer education

There are a few differences between a computer applications engineer and a data engineer in terms of educational background:

Computer Applications EngineerData Engineer
Most common degreeBachelor's Degree, 63%Bachelor's Degree, 65%
Most common majorElectrical EngineeringComputer Science
Most common collegeStanford UniversityCalifornia State University - Long Beach

Computer applications engineer vs data engineer demographics

Here are the differences between computer applications engineers' and data engineers' demographics:

Computer Applications EngineerData Engineer
Average age3939
Gender ratioMale, 81.9% Female, 18.1%Male, 81.5% Female, 18.5%
Race ratioBlack or African American, 4.6% Unknown, 4.8% Hispanic or Latino, 8.3% Asian, 25.3% White, 56.8% American Indian and Alaska Native, 0.2%Black or African American, 4.3% Unknown, 4.8% Hispanic or Latino, 8.0% Asian, 30.1% White, 52.7% American Indian and Alaska Native, 0.2%
LGBT Percentage8%8%

Differences between computer applications engineer and data engineer duties and responsibilities

Computer applications engineer example responsibilities.

  • Manage RF servers and performing network troubleshooting and preventative maintenance on network elements.
  • Experience with Fanuc, Bridgeport and Heidenhain controls.
  • Guide the PC board development of a switching converter EMI reduction research team.
  • Design data models, database tables and data access routines for the Chrysler CAD/CAM system's IGES translators.
  • Work with development teams to troubleshoot development environment, production environment, performance tuning and optimize code.
  • Expedite and simplify the quotation process for solar water heating systems by accurately representing solar water heating system performance through MATLAB models
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Data engineer example responsibilities.

  • Used SQOOP to import the data from RDBMS to HDFS to achieve the reliability of data.
  • Develop automation scripts in python to automate the test, analyze, plot and report the results.
  • Used Linux shell scripts to automate the build process, and to perform regular jobs like file transfers between different hosts.
  • Increase audit efficiency by developing SAS programs to automate manual testing procedures.
  • Used Teradata database management system to manage the warehousing operations and parallel processing.
  • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
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Computer applications engineer vs data engineer skills

Common computer applications engineer skills
  • FANUC, 24%
  • Machine Tools, 24%
  • CAD/CAM, 18%
  • Linux, 13%
  • Technical Support, 12%
  • Training Classes, 4%
Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%

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