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Lead data technician vs senior data technician

The differences between lead data technicians and senior data technicians can be seen in a few details. Each job has different responsibilities and duties. It typically takes 6-12 months to become both a lead data technician and a senior data technician. Additionally, a lead data technician has an average salary of $124,928, which is higher than the $89,734 average annual salary of a senior data technician.

The top three skills for a lead data technician include python, architecture and java. The most important skills for a senior data technician are emerging technologies, data management, and SQL.

Lead data technician vs senior data technician overview

Lead Data TechnicianSenior Data Technician
Yearly salary$124,928$89,734
Hourly rate$60.06$43.14
Growth rate7%7%
Number of jobs83,45579,151
Job satisfaction--
Most common degreeBachelor's Degree, 50%Bachelor's Degree, 49%
Average age3838
Years of experience1212

Lead data technician vs senior data technician salary

Lead data technicians and senior data technicians have different pay scales, as shown below.

Lead Data TechnicianSenior Data Technician
Average salary$124,928$89,734
Salary rangeBetween $92,000 And $169,000Between $52,000 And $153,000
Highest paying CitySan Francisco, CA-
Highest paying stateAlaska-
Best paying companyMeta-
Best paying industryInsurance-

Differences between lead data technician and senior data technician education

There are a few differences between a lead data technician and a senior data technician in terms of educational background:

Lead Data TechnicianSenior Data Technician
Most common degreeBachelor's Degree, 50%Bachelor's Degree, 49%
Most common majorComputer ScienceBusiness
Most common collegeStanford UniversityStanford University

Lead data technician vs senior data technician demographics

Here are the differences between lead data technicians' and senior data technicians' demographics:

Lead Data TechnicianSenior Data Technician
Average age3838
Gender ratioMale, 76.1% Female, 23.9%Male, 58.3% Female, 41.7%
Race ratioBlack or African American, 9.3% Unknown, 6.0% Hispanic or Latino, 16.5% Asian, 11.9% White, 55.2% American Indian and Alaska Native, 1.1%Black or African American, 9.4% Unknown, 5.7% Hispanic or Latino, 16.6% Asian, 10.5% White, 56.8% American Indian and Alaska Native, 1.0%
LGBT Percentage8%8%

Differences between lead data technician and senior data technician duties and responsibilities

Lead data technician example responsibilities.

  • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
  • Create database queries and run SQL scripts to generate reports for data analysis.
  • Configure Bios and Linux through command line remotely and on site.
  • Perform QA checks on criminal expungement/modification and VIPs on a monthly basis.
  • Convert and reformat several PDF files to convenient CD-ROMS for field use.
  • Create data models using star schema methodology and create and schedule ETL processes.
  • Show more

Senior data technician example responsibilities.

  • Manage clinical trials by gathering data, monitoring adverse events, screening patients for eligibility and scheduling patients per protocol.
  • Prepare data and update databases with information from QC checks, audits, data change forms, and site monitoring.
  • Implement action plans including performing require upgrades and installation of PC's and require peripheral equipment.
  • Manage clinical trials by gathering data, monitoring adverse events, screening patients for eligibility and scheduling patients per protocol.
  • Coordinate daily scrum meeting with project team members helping to facilitate communication, maximize productivity and resolve issues early.

Lead data technician vs senior data technician skills

Common lead data technician skills
  • Python, 10%
  • Architecture, 9%
  • Java, 8%
  • Spark, 7%
  • Data Lake, 6%
  • Hadoop, 6%
Common senior data technician skills
  • Emerging Technologies, 23%
  • Data Management, 10%
  • SQL, 10%
  • Troubleshoot, 8%
  • Data Collection, 7%
  • Data Processing, 7%

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