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Full Time Data Annotation Tech information

See Boulder, CO salary details

$12

$23

$36

How much do full time data annotation tech jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for full time data annotation tech in Boulder, CO is $23.69, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $28.17 per hour, depending on experience, location, and employer.

What is a full time data annotation tech?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a full time data annotation tech?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

How does a full time data annotation tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What is the difference between Full Time Data Annotation Tech vs Data Labeling Specialist?

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Does full time data annotation tech actually pay?

Full-time data annotation technicians typically receive a regular salary or hourly wage, with pay rates varying based on experience, location, and company. Many roles offer benefits such as paid time off and health insurance, and some positions may require familiarity with annotation tools or specific data types.

What are popular job titles related to Full Time Data Annotation Tech jobs in Boulder, CO?

For Full Time Data Annotation Tech jobs in Boulder, CO, the most frequently searched job titles are:

What job categories do people searching Full Time Data Annotation Tech jobs in Boulder, CO look for?

The top searched job categories for Full Time Data Annotation Tech jobs in Boulder, CO are:

Full Time Data Annotation Tech jobs near you
Infographic showing various Full Time Data Annotation Tech job openings in Boulder, CO as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $49,275 per year, or $23.7 per hour.

Title Sr. Manager, Data Engineering | Full-Time | Denver Tech Center

Oak View Group

Denver, CO

$150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

Oak View Group rating

6.2

Company rating: 6.2 out of 10

Based on 83 frontline employees who took The Breakroom Quiz

24th of 37 rated event venues

Job description

Sr. Manager, Data Engineering | Full-Time | Denver Tech Center
Location US-CO-Denver
Job Post Information* : Posted Date 2 weeks ago(8/4/2026 4:17 PM)
Job ID 2026-33537
Category Marketing
Type Regular Full-Time
Location : Location US-CO-Denver
Job Post Information* : External Company Name Oak View Group
Job Post Information* : External Company URL https://www.oakviewgroup.com/
Location : Postal Code 80237
Location : Address 5050 S. Syracuse St, 8th Floor
Job Post Information* : Post End Date 11/6/2026
Overview

Oak View Group is hiring a Sr. Manager, Data Engineering based in Denver, CO, reporting to the Sr. Director, Data & Analytics. As we continue to grow and redefine the landscape of sports, live entertainment, and hospitality, Oak View Group is evolving the pivotal role of Sr. Manager, Data Engineering to lead both the development of our data platform and a growing team of data engineers. This individual will be instrumental in architecting and executing data strategies that empower our business with actionable insights, fostering a culture of data-driven decision-making across our global operations. The Sr. Manager, Data Engineering will bring deep technical expertise and strong people leadership to drive the development and optimization of our data infrastructure, systems, and analytics capabilities. They will employ agile methodologies to adapt to and anticipate the needs of our rapidly evolving business landscape, while ensuring team alignment, delivery excellence, and scalable growth of our data platform.

This role pays an annual salary of $150,000 and is bonus eligible.

Benefits for Full-Time roles: Health, Dental and Vision Insurance, 401(k) Savings Plan, 401(k) matching, and Paid Time Off (vacation days, sick days, and 11 holidays)

This position will remain open until November 6, 2026.

Responsibilities
  • Architect, develop, and optimize data pipelines, databases, and analytics platforms within Azure to support business intelligence, data science, and operational applications.
  • Lead and manage a team of 1-3 data engineers, providing mentorship, technical guidance, and performance management to drive high-quality execution and career development.
  • Own the data engineering roadmap, prioritizing integrations, platform enhancements, and scalability initiatives aligned with business goals.
  • Collaborate with stakeholders across the organization to understand data needs, deliver solutions that drive business value, and align efforts with the company's strategic objectives.
  • Implement and scale agile data engineering practices, adapting to business shifts and technological advancements with flexibility and foresight.
  • Champion a culture of data-driven decision-making, ensuring data quality, governance, and security standards are upheld.
  • Establish best practices for code quality, data modeling, testing, and deployment, improving the reliability and maintainability of the data platform.
  • Foster and manage relationships with external partners and vendors, ensuring seamless integration of their services and technologies into our data infrastructure to enhance our capabilities and drive innovation.
Qualifications
  • Bachelor's degree in computer science, engineering, or a related field.
  • 4-6+ years of data engineering experience.
  • Ability to manage a small team while remaining hands-on.
  • Proficient in data engineering tools, ETL processes, APIs, and data warehousing, with a proven ability to develop and manage efficient data pipelines.
  • Familiarity with Azure cloud services, showcasing the ability to utilize Azure's data services to create scalable and secure data solutions.
  • Effective collaboration with analytics, business intelligence, and IT teams to align data solutions with organizational objectives.
  • Experience with data governance, security practices, and compliance regulations.
  • Demonstrated experience in balancing multiple projects simultaneously, with a track record of meeting deadlines and business goals.
  • Strong communication skills, with the ability to translate technical concepts into business impact.
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