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The differences between integration engineers and data engineers can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 4-6 years to become an integration engineer, becoming a data engineer takes usually requires 2-4 years. Additionally, a data engineer has an average salary of $109,675, which is higher than the $99,674 average annual salary of an integration engineer.
The top three skills for an integration engineer include python, java and data analysis. The most important skills for a data engineer are python, java, and cloud.
| Integration Engineer | Data Engineer | |
| Yearly salary | $99,674 | $109,675 |
| Hourly rate | $47.92 | $52.73 |
| Growth rate | 2% | 21% |
| Number of jobs | 103,437 | 303,105 |
| Job satisfaction | - | - |
| Most common degree | Bachelor's Degree, 67% | Bachelor's Degree, 65% |
| Average age | 41 | 39 |
| Years of experience | 6 | 4 |
An integration engineer specializes in developing programs and projects to improve business systems for optimal processes. Their responsibilities revolve around meeting with clients to determine their needs, coordinating with analysts to identify the company's strengths and weaknesses, implementing various solutions for business processes, and performing corrective measures as needed. They must also respond to any issues or inquiries, resolving them promptly and professionally. Furthermore, an integration manager may perform clerical tasks such as processing and preparing documentation, performing presentations, and updating clients.
A data engineer is someone who makes data science possible. This IT job requires the search for data set trends and algorithm development to make raw data more beneficial to the enterprise. Data engineers are responsible for establishing and maintaining an environment that permits other data functions. The necessary skills for the job include in-depth knowledge of multiple programming languages and SQL database design. Among the other skills data engineers should develop include data warehousing and architecture, data mining and modeling, and statistical regression analysis.
Integration engineers and data engineers have different pay scales, as shown below.
| Integration Engineer | Data Engineer | |
| Average salary | $99,674 | $109,675 |
| Salary range | Between $74,000 And $133,000 | Between $80,000 And $149,000 |
| Highest paying City | San Francisco, CA | San Francisco, CA |
| Highest paying state | California | California |
| Best paying company | Meta | The Citadel |
| Best paying industry | Telecommunication | Technology |
There are a few differences between an integration engineer and a data engineer in terms of educational background:
| Integration Engineer | Data Engineer | |
| Most common degree | Bachelor's Degree, 67% | Bachelor's Degree, 65% |
| Most common major | Electrical Engineering | Computer Science |
| Most common college | Massachusetts Institute of Technology | California State University - Long Beach |
Here are the differences between integration engineers' and data engineers' demographics:
| Integration Engineer | Data Engineer | |
| Average age | 41 | 39 |
| Gender ratio | Male, 85.2% Female, 14.8% | Male, 81.5% Female, 18.5% |
| Race ratio | Black or African American, 3.1% Unknown, 4.5% Hispanic or Latino, 7.8% Asian, 16.7% White, 67.8% American Indian and Alaska Native, 0.1% | 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 Percentage | 5% | 8% |