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Data modeler vs data engineer

The differences between data modelers 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 data modeler and a data engineer. Additionally, a data engineer has an average salary of $109,675, which is higher than the $100,495 average annual salary of a data modeler.

The top three skills for a data modeler include ETL, data analysis and data architecture. The most important skills for a data engineer are python, java, and cloud.

Data modeler vs data engineer overview

Data ModelerData Engineer
Yearly salary$100,495$109,675
Hourly rate$48.31$52.73
Growth rate9%21%
Number of jobs81,645303,105
Job satisfaction--
Most common degreeBachelor's Degree, 70%Bachelor's Degree, 65%
Average age4639
Years of experience44

What does a data modeler do?

A data modeler is responsible for designing and creating network systems and applications for efficient and secured data storage solutions. Data modelers work closely with the data management team to identify business needs and execute data modeling techniques for comprehensive analysis. They also strategize in improving existing data systems, upgrading infrastructure, and configuring information for compatibility with every business unit. A data modeler must have excellent technical skills, as well as a strong command of programming languages to modify and optimize data models for smooth navigation and access.

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.

Data modeler vs data engineer salary

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

Data ModelerData Engineer
Average salary$100,495$109,675
Salary rangeBetween $73,000 And $138,000Between $80,000 And $149,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaCalifornia
Best paying companyMetaThe Citadel
Best paying industryPharmaceuticalTechnology

Differences between data modeler and data engineer education

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

Data ModelerData Engineer
Most common degreeBachelor's Degree, 70%Bachelor's Degree, 65%
Most common majorComputer ScienceComputer Science
Most common college-California State University - Long Beach

Data modeler vs data engineer demographics

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

Data ModelerData Engineer
Average age4639
Gender ratioMale, 71.0% Female, 29.0%Male, 81.5% Female, 18.5%
Race ratioBlack or African American, 6.2% Unknown, 5.1% Hispanic or Latino, 8.1% Asian, 28.6% White, 51.5% American Indian and Alaska Native, 0.5%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 Percentage6%8%

Differences between data modeler and data engineer duties and responsibilities

Data modeler example responsibilities.

  • Lead efforts to analyze data for source/target mappings, create T-SQL scripts for data processing.
  • Involve in data governance processes relate to data quality and information management, managing the metadata repository etc.
  • Accomplish at designing dashboards and data summaries for technical and non-technical audiences and facilitating implementation of business strategies and missions.
  • Design the data marts in dimensional data modeling using star and snowflake schemas.
  • Develop data architecture prototypes and data models including ETL staging models, audit control models and traditional data warehouse dimension/fact models.
  • Work extensively with XML schema generation.
  • 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

Data modeler vs data engineer skills

Common data modeler skills
  • ETL, 6%
  • Data Analysis, 6%
  • Data Architecture, 6%
  • Physical Data Models, 5%
  • Data Warehouse, 5%
  • Tableau, 5%
Common data engineer skills
  • Python, 12%
  • Java, 9%
  • Cloud, 5%
  • ETL, 5%
  • Scala, 4%
  • Kafka, 4%

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