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Data engineer vs machining engineer

The differences between data engineers and machining engineers can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 2-4 years to become a data engineer, becoming a machining engineer takes usually requires 4-6 years. Additionally, a machining engineer has an average salary of $123,716, which is higher than the $109,675 average annual salary of a data engineer.

The top three skills for a data engineer include python, java and cloud. The most important skills for a machining engineer are python, java, and tensorflow.

Data engineer vs machining engineer overview

Data EngineerMachining Engineer
Yearly salary$109,675$123,716
Hourly rate$52.73$59.48
Growth rate21%2%
Number of jobs303,10593,823
Job satisfaction--
Most common degreeBachelor's Degree, 65%Bachelor's Degree, 53%
Average age3941
Years of experience46

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.

What does a machining engineer do?

A machining engineer specializes in designing and developing new tools and mechanical equipment, even analyzing and improving designs to ensure efficiency. Their responsibilities revolve around overseeing and participating in installing, repairing, and maintaining different systems, coordinating with other engineers, and conducting regular inspections to monitor a machines' quality. It is also essential to address any issues or concerns, performing corrective measures right away. Furthermore, should a machining engineer work for a company, it is necessary to adhere to its policies and regulations.

Data engineer vs machining engineer salary

Data engineers and machining engineers have different pay scales, as shown below.

Data EngineerMachining Engineer
Average salary$109,675$123,716
Salary rangeBetween $80,000 And $149,000Between $83,000 And $182,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaCalifornia
Best paying companyThe CitadelAirbnb
Best paying industryTechnologyStart-up

Differences between data engineer and machining engineer education

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

Data EngineerMachining Engineer
Most common degreeBachelor's Degree, 65%Bachelor's Degree, 53%
Most common majorComputer ScienceElectrical Engineering
Most common collegeCalifornia State University - Long BeachMassachusetts Institute of Technology

Data engineer vs machining engineer demographics

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

Data EngineerMachining Engineer
Average age3941
Gender ratioMale, 81.5% Female, 18.5%Male, 93.5% Female, 6.5%
Race ratioBlack 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%Black or African American, 3.4% Unknown, 4.6% Hispanic or Latino, 9.1% Asian, 14.9% White, 68.0% American Indian and Alaska Native, 0.1%
LGBT Percentage8%5%

Differences between data engineer and machining engineer duties and responsibilities

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.
  • Show more

Machining engineer example responsibilities.

  • Lead and manage CNC production line including support as required in engineering, material and quality control.
  • Manage Jenkins security by providing specific access to authorize developers/testers using project base matrix authorization strategy.
  • Cross-Connect the cable python to the Mervyns network rack.
  • Research extended axes to be integrate with the FANUC control system.
  • Select controller for high positional accuracy for precision pointing of LIDAR.
  • Used Microsoft SQL server reporting services (SSRS) for data reporting.
  • Show more

Data engineer vs machining engineer skills

Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%
Common machining engineer skills
  • Python, 22%
  • Java, 20%
  • TensorFlow, 11%
  • Spark, 10%
  • Deep Learning, 10%
  • C++, 6%

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