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Etl lead vs data warehouse developer

The differences between etl leads and data warehouse developers can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 4-6 years to become an etl lead, becoming a data warehouse developer takes usually requires 2-4 years. Additionally, an etl lead has an average salary of $106,442, which is higher than the $93,381 average annual salary of a data warehouse developer.

The top three skills for an etl lead include sql server, architecture and data warehouse. The most important skills for a data warehouse developer are ETL, java, and hadoop.

Etl lead vs data warehouse developer overview

ETL LeadData Warehouse Developer
Yearly salary$106,442$93,381
Hourly rate$51.17$44.89
Growth rate9%21%
Number of jobs31,461194,780
Job satisfaction--
Most common degreeBachelor's Degree, 71%Bachelor's Degree, 68%
Average age4339
Years of experience64

Etl lead vs data warehouse developer salary

Etl leads and data warehouse developers have different pay scales, as shown below.

ETL LeadData Warehouse Developer
Average salary$106,442$93,381
Salary rangeBetween $83,000 And $135,000Between $72,000 And $120,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateWashingtonCalifornia
Best paying companyNerdWalletThe Citadel
Best paying industryHealth CareInsurance

Differences between etl lead and data warehouse developer education

There are a few differences between an etl lead and a data warehouse developer in terms of educational background:

ETL LeadData Warehouse Developer
Most common degreeBachelor's Degree, 71%Bachelor's Degree, 68%
Most common majorComputer ScienceComputer Science
Most common collegeMassachusetts Institute of TechnologyMassachusetts Institute of Technology

Etl lead vs data warehouse developer demographics

Here are the differences between etl leads' and data warehouse developers' demographics:

ETL LeadData Warehouse Developer
Average age4339
Gender ratioMale, 74.2% Female, 25.8%Male, 68.4% Female, 31.6%
Race ratioBlack or African American, 8.2% Unknown, 4.9% Hispanic or Latino, 9.6% Asian, 25.6% White, 51.4% American Indian and Alaska Native, 0.2%Black or African American, 4.4% Unknown, 4.8% Hispanic or Latino, 8.1% Asian, 30.0% White, 52.6% American Indian and Alaska Native, 0.2%
LGBT Percentage8%8%

Differences between etl lead and data warehouse developer duties and responsibilities

Etl lead example responsibilities.

  • Manage the issues raise from QA and assign work items to the team and take up critical work items.
  • Lead defect review meetings with business team leads as well as QA lead and prioritize development tasks around project milestones.
  • Involve in writing UNIX shell scripts and automate the sessions running processes and also write UNIX Perl scripts for business needs.
  • Provide technical leadership and manage all aspects of the SDLC process-requirement analysis, design, development, testing, and support/maintenance.
  • Administrate SharePoint database access; manage classified documents and applications.
  • Involve in writing TeraData scripts.
  • Show more

Data warehouse developer example responsibilities.

  • Help in set up the SharePoint server, deploy reports and create, manage subscriptions and data driven subscriptions.
  • Achieve significant performance improvement in reducing response time of queries by rewriting and tuning SQL statements embed in PhP code.
  • Develop MapReduce jobs in Java API to parse the raw data and store the refined data.
  • Shell scripting, Linux administration, and Perl language support.
  • Develop, modify and execute Perl and MySQL scripts from Linux command line.
  • Liaise with QA in deploying ETL flows and reports into their environments and attend defect calls.
  • Show more

Etl lead vs data warehouse developer skills

Common etl lead skills
  • SQL Server, 6%
  • Architecture, 5%
  • Data Warehouse, 5%
  • Unix, 5%
  • Data Quality, 4%
  • Informatica Powercenter, 4%
Common data warehouse developer skills
  • ETL, 8%
  • Java, 7%
  • Hadoop, 6%
  • Data Warehouse, 6%
  • Visualization, 5%
  • Data Analysis, 5%

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