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Deployment engineer vs data engineer

The differences between deployment 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 deployment engineer and a data engineer. Additionally, a data engineer has an average salary of $109,675, which is higher than the $100,911 average annual salary of a deployment engineer.

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

Deployment engineer vs data engineer overview

Deployment EngineerData Engineer
Yearly salary$100,911$109,675
Hourly rate$48.51$52.73
Growth rate21%21%
Number of jobs254,721303,105
Job satisfaction--
Most common degreeBachelor's Degree, 62%Bachelor's Degree, 65%
Average age3939
Years of experience44

What does a deployment engineer do?

A deployment engineer specializes in designing and developing deployment systems, ensuring quality and efficiency. Typically, it is their duty to conduct research and analysis to identify the company's needs, assess existing systems to identify areas needing improvement, implementing solutions against problem areas, and developing strategies to optimize operations. They may also provide technical support to employees, spearhead training programs as required. Furthermore, as a deployment engineer, it is essential to lead and encourage the staff to reach goals while implementing the company's policies and regulations.

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.

Deployment engineer vs data engineer salary

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

Deployment EngineerData Engineer
Average salary$100,911$109,675
Salary rangeBetween $74,000 And $136,000Between $80,000 And $149,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaCalifornia
Best paying companyMetaThe Citadel
Best paying industryTechnologyTechnology

Differences between deployment engineer and data engineer education

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

Deployment EngineerData Engineer
Most common degreeBachelor's Degree, 62%Bachelor's Degree, 65%
Most common majorComputer ScienceComputer Science
Most common collegeCalifornia State University - Long BeachCalifornia State University - Long Beach

Deployment engineer vs data engineer demographics

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

Deployment EngineerData Engineer
Average age3939
Gender ratioMale, 89.8% Female, 10.2%Male, 81.5% Female, 18.5%
Race ratioBlack or African American, 4.5% Unknown, 4.8% Hispanic or Latino, 8.2% Asian, 29.9% White, 52.4% 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 deployment engineer and data engineer duties and responsibilities

Deployment engineer example responsibilities.

  • Create service requests in CRM application to reflect report issues and manage customer expectations throughout escalation and/or resolution.
  • Complete core/handler Java programming, JSP development, and QA testing responsibilities.
  • Research and adopt optimal Linux OS configurations to provide better server performance.
  • Work on TWS migration for entire ETL jobs
  • Help to design and deploy a VMWare base private cloud.
  • Maintain UNIX share library and windows DLL code for product lines.
  • 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.
  • Show more

Deployment engineer vs data engineer skills

Common deployment engineer skills
  • Python, 8%
  • Troubleshoot, 7%
  • Linux, 6%
  • Java, 5%
  • Windows Server, 4%
  • Desktop, 4%
Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%

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