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Application integration engineer vs data engineer

The differences between application integration 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 an application integration engineer and a data engineer. Additionally, a data engineer has an average salary of $109,675, which is higher than the $103,379 average annual salary of an application integration engineer.

The top three skills for an application integration engineer include java, project management and application integration. The most important skills for a data engineer are python, java, and cloud.

Application integration engineer vs data engineer overview

Application Integration EngineerData Engineer
Yearly salary$103,379$109,675
Hourly rate$49.70$52.73
Growth rate21%21%
Number of jobs139,788303,105
Job satisfaction--
Most common degreeBachelor's Degree, 61%Bachelor's Degree, 65%
Average age3939
Years of experience44

Application integration engineer vs data engineer salary

Application integration engineers and data engineers have different pay scales, as shown below.

Application Integration EngineerData Engineer
Average salary$103,379$109,675
Salary rangeBetween $80,000 And $133,000Between $80,000 And $149,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateMassachusettsCalifornia
Best paying companyGoogleThe Citadel
Best paying industryPharmaceuticalTechnology

Differences between application integration engineer and data engineer education

There are a few differences between an application integration engineer and a data engineer in terms of educational background:

Application Integration EngineerData Engineer
Most common degreeBachelor's Degree, 61%Bachelor's Degree, 65%
Most common majorElectrical EngineeringComputer Science
Most common collegeStanford UniversityCalifornia State University - Long Beach

Application integration engineer vs data engineer demographics

Here are the differences between application integration engineers' and data engineers' demographics:

Application Integration EngineerData Engineer
Average age3939
Gender ratioMale, 85.9% Female, 14.1%Male, 81.5% Female, 18.5%
Race ratioBlack or African American, 4.6% Unknown, 4.8% Hispanic or Latino, 8.4% Asian, 29.8% White, 52.2% 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 application integration engineer and data engineer duties and responsibilities

Application integration engineer example responsibilities.

  • Focuse on delivering engine, air handling, after-treatment and controls architecture recommendations to achieve cost reduction and fuel economy improvements.
  • Provide technical support and troubleshoot issues relate to XML configurations, SSL certificates, and network relate issues.
  • Port an OpenVMS application to Tru64 Unix using Korn shell scripting.
  • Develop XSL for integrating the XML output for printing over the base document.
  • Support and troubleshoot service provisioning functions.
  • Migrate a telecommunications application over to Tru64 Unix.
  • Show more

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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Application integration engineer vs data engineer skills

Common application integration engineer skills
  • Java, 18%
  • Project Management, 10%
  • Application Integration, 9%
  • API, 8%
  • Application Development, 6%
  • Application Issues, 5%
Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%

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