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Remote Data Tagging Jobs (NOW HIRING)

Samprasoft

Data Engineer II

Miami, FL · On-site +1

$109.50K - $131.50K/yr

This is a remote role at this time but will require hybrid work in Miami, Florida by end of this ... Turning unstructured data into useful information by auto-tagging images and text-to-speech ...

Zeta Global

Client Experience Operations Manager

$70K - $85K/yr

This role sits at the intersection of media strategy, analytics, and data cloud, ensuring ... Digital Tagging & Tracking * Support implementation and QA of tracking tags across media platforms ...

Arctiq

IAM Specialist - Remote Contract

Blue Bell, PA · Remote

Identify and inventory local data plane resources (user/keys/roles/policies/groups) and manage ... Develop a comprehensive metadata tagging strategy mapped to ASL, environment, and repository ...

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$55K

$99.2K

$135.5K

How much do remote data tagging jobs pay per year?

As of Jun 1, 2026, the average yearly pay for remote data tagging in the United States is $99,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $108,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Tagging Specialist, and why are they important?

To thrive as a Remote Data Tagging Specialist, you need strong attention to detail, basic data analysis skills, and familiarity with data labeling concepts, typically supported by a high school diploma or higher. Experience with data annotation tools such as Labelbox, Supervisely, or CVAT, and understanding of formats like JSON or XML, is commonly required. Excellent time management, communication, and reliability are standout soft skills for this remote role. These abilities are crucial to ensure high-quality, accurate datasets that power machine learning and AI systems.

What are some common challenges faced by remote data tagging professionals and how can they be addressed?

Remote data tagging professionals often encounter challenges such as maintaining consistent accuracy, managing repetitive tasks, and staying engaged without in-person supervision. To address these, it’s helpful to follow clear annotation guidelines, take regular breaks to prevent fatigue, and use collaboration tools to communicate with team members or supervisors. Many organizations also provide feedback loops and quality checks to support remote taggers in improving their work and staying aligned with project expectations.

What is remote data tagging?

Remote data tagging is the process of labeling or annotating data—such as images, videos, text, or audio—while working from a remote location, typically from home. This work is essential for training artificial intelligence (AI) and machine learning models, as it helps computers better understand and categorize information. Data taggers use specialized software to mark, classify, or add metadata to various types of digital content according to specific guidelines provided by employers or clients. Most remote data tagging jobs require attention to detail, basic computer skills, and the ability to follow detailed instructions. These roles are often offered as freelance, part-time, or full-time remote positions.

What jobs make $3,000 a month without a degree?

Remote data tagging jobs can pay around $3,000 per month for individuals who have strong attention to detail and basic computer skills. These roles often require minimal formal education, rely on online platforms, and may involve flexible schedules, making them accessible for those without a degree.

What is the difference between Remote Data Tagging vs Remote Data Annotation?

AspectRemote Data TaggingRemote Data Annotation
Primary FocusLabeling specific data points within datasetsAdding detailed labels and context to data
Skills RequiredAttention to detail, basic understanding of data typesAnalytical skills, understanding of data context
Work EnvironmentRemote, often part-time or freelanceRemote, often part-time or freelance
Industry UsageMachine learning, AI trainingMachine learning, AI training

Remote Data Tagging and Remote Data Annotation are closely related tasks in AI data preparation. Tagging typically involves marking specific data points, while annotation provides more detailed context. Both roles are essential for training machine learning models and share similar skills and work environments.

More about Remote Data Tagging jobs
What cities are hiring for Remote Data Tagging jobs? Cities with the most Remote Data Tagging job openings:
What are the most commonly searched types of Data Tagging jobs? The most popular types of Data Tagging jobs are:
What states have the most Remote Data Tagging jobs? States with the most job openings for Remote Data Tagging jobs include:
What job categories do people searching Remote Data Tagging jobs look for? The top searched job categories for Remote Data Tagging jobs are:
Remote Data Tagging jobs near you
Infographic showing various Remote Data Tagging job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $99,231 per year, or $47.7 per hour.
Data Engineer II

Data Engineer II

Samprasoft

Miami, FL • On-site, Remote

$109.50K - $131.50K/yr

Other

Posted 20 days ago

Job description

Data Engineer Opportunity

Our client has a one year + contract role for a Data Engineer in Miami, FL. This is a remote role at this time but will require hybrid work in Miami, Florida by end of this year. This is a mid level role and not looking for Senior candidates.

Join a fast-growing team

As a Data Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data.

You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.

Your Role
  • Drive the evolution of Data & Services products/platforms with an impact-focused on data science and engineering
  • Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
  • Ensuring that algorithms generate accurate user recommendations.
  • Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers.
  • Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
  • Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and expand the ways and properties on which we can test
  • Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
  • Maintain awareness of relevant technical and product trends through self-learning/study, training classes and job shadowing.
  • Participate in the development of data and analytic infrastructure for product development
  • Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations
  • Partner with roles across the organization including consultants, engineering, and sales to determine the highest priority problems to solve
  • Evaluate trade-offs between many possible analytics solutions to a problem, taking into account usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision
  • Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients, and other stakeholders
  • Evangelize releases to users, incorporating feedback, and tracking usage to inform future development
  • Work with small, cross-functional teams to define the vision, establish team culture and processes
  • Consistently focus on key drivers of organization value and prioritize operational activities accordingly
  • Escalate technical errors or bugs detected in project work
  • Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing.

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