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Management engineer vs data engineer

The differences between management 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 a management 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 $90,571 average annual salary of a management engineer.

The top three skills for a management engineer include infrastructure, java and linux. The most important skills for a data engineer are python, java, and cloud.

Management engineer vs data engineer overview

Management EngineerData Engineer
Yearly salary$90,571$109,675
Hourly rate$43.54$52.73
Growth rate2%21%
Number of jobs175,986303,105
Job satisfaction--
Most common degreeBachelor's Degree, 69%Bachelor's Degree, 65%
Average age4139
Years of experience64

What does a management engineer do?

A management engineer specializes in designing and developing systems to optimize business or establishment procedures. Their duties typically revolve around coordinating with various departments to obtain necessary data, conducting observations and inspections to determine the strengths and weaknesses of existing processes, executing maintenance checks to ensure the efficiency of services, and performing research and analysis to come up with the ideal solutions. Furthermore, as a management engineer, it is essential to adhere to the company's policies and regulations when making decisions or recommending new systems.

What does a data engineer do?

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.

Management engineer vs data engineer salary

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

Management EngineerData Engineer
Average salary$90,571$109,675
Salary rangeBetween $65,000 And $125,000Between $80,000 And $149,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaCalifornia
Best paying companyAppleThe Citadel
Best paying industryTechnologyTechnology

Differences between management engineer and data engineer education

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

Management EngineerData Engineer
Most common degreeBachelor's Degree, 69%Bachelor's Degree, 65%
Most common majorMechanical EngineeringComputer Science
Most common collegeNorthwestern UniversityCalifornia State University - Long Beach

Management engineer vs data engineer demographics

Here are the differences between management engineers' and data engineers' demographics:

Management EngineerData Engineer
Average age4139
Gender ratioMale, 81.2% Female, 18.8%Male, 81.5% Female, 18.5%
Race ratioBlack or African American, 3.3% Unknown, 4.6% Hispanic or Latino, 9.0% Asian, 14.9% White, 68.1% 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 Percentage5%8%

Differences between management engineer and data engineer duties and responsibilities

Management engineer example responsibilities.

  • Manage, troubleshoot and test the production batch processes from both an application and system stand point includes new installs.
  • Collaborate with team effort to remotely manage customers Avamar Linux data storage servers.
  • Engage in developing database for efficiently managing and tracking work orders within departments.
  • Manage Jenkins security by providing specific access to authorize developers/testers using project base matrix authorization strategy.
  • Monitor, troubleshoot, and resolve system/service failures.
  • Script builds of Redhat LINUX and Solaris servers along with baselinesoftware.
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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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Management engineer vs data engineer skills

Common management engineer skills
  • Infrastructure, 11%
  • Java, 8%
  • Linux, 6%
  • Project Management, 6%
  • Azure, 5%
  • LDAP, 4%
Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%

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