ZipRecruiter

Log In

1

Virtual Data Labelling Jobs (NOW HIRING)

Buyers Edge Platform, LLC

Tableau Data Architect

Waltham, MA · Remote

$68.75 - $88.50/hr

... labels), metric governance via Tableau Pulse, and enforcement of naming conventions, access ... Design and manage Virtual Connections and published data sources to centralize data access and ...

Diverse Lynx

Lead Data Center Technician

Dallas, TX

They operate in tight spaces, run & label cabling, and improve physical security around their ... They also create concise virtual information reports to keep company management informed of status ...

next page

Showing results 1-20

All JobsVirtual Data Labelling Jobs

Virtual Data Labelling information

See salary details

$46K

$165K

$243.5K

How much do virtual data labelling jobs pay per year?

As of Jun 21, 2026, the average yearly pay for virtual data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Virtual Data Labelling vs Data Annotation Specialist?

AspectVirtual Data LabellingData Annotation Specialist
CredentialsBasic computer skills, training in labelling toolsSimilar, often requires training in annotation software
Work EnvironmentRemote, online platformsRemote or on-site, depending on employer
Industry UsageAI, machine learning, autonomous vehiclesAI, computer vision, NLP projects
Search IntentLabeling data for AI modelsAnnotating data for machine learning

Both roles involve preparing data for AI systems, but Virtual Data Labelling focuses on assigning labels to datasets using online tools, while Data Annotation Specialists may perform more detailed annotations, often requiring specific domain knowledge. Both are essential in AI development and share similar work environments and skill requirements.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Many roles are freelance or part-time, with some positions offering bonuses for accuracy or speed.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning, offering opportunities to develop skills in data management and understanding AI workflows. It often requires attention to detail and familiarity with tools like annotation software, with flexible schedules and remote work options available. Career growth can lead to roles in data analysis, quality assurance, or AI development.

What is virtual data labelling?

Virtual data labelling is the process of annotating or tagging data, such as images, videos, or text, through online platforms to make it understandable for machine learning algorithms. Data labelers work remotely to identify and categorize objects, features, or information within datasets, which helps train artificial intelligence systems. This job is essential in industries like autonomous vehicles, healthcare, and e-commerce, where large volumes of labelled data are needed to improve AI accuracy.

How can I make $2000 a week working from home?

Virtual data labeling jobs can offer flexible income, but earning $2000 weekly typically requires completing a high volume of tasks or working multiple projects simultaneously. Success depends on experience, efficiency, and access to platforms that pay well, such as those offering premium or specialized labeling tasks.

How to make $1000 a week remote?

Virtual Data Labelling jobs can help you earn income remotely by labeling datasets for AI and machine learning projects. To make $1000 a week, you typically need to work consistently, complete high-volume labeling tasks efficiently, and possibly specialize in areas like image or audio annotation. Building a strong profile, gaining experience, and using platforms that pay well can increase your earning potential.

How does a virtual data labeller typically collaborate with data scientists and machine learning engineers?

Virtual data labellers play a crucial role in supporting data scientists and machine learning engineers by accurately tagging data that will be used to train and validate models. Collaboration often occurs through project management tools or direct communication platforms, where labellers receive guidelines and feedback to ensure consistency and quality. Regular check-ins or quality audits are common, and labellers may join virtual meetings to clarify requirements or discuss ambiguous cases. This teamwork helps ensure that the labelled data meets project standards and contributes to the success of AI initiatives.

What are the key skills and qualifications needed to thrive as a Virtual Data Labeller, and why are they important?

To thrive as a Virtual Data Labeller, you need strong attention to detail, accuracy, and basic data processing skills, typically supported by a high school diploma or relevant experience. Familiarity with data annotation tools, content management systems, and sometimes basic programming or spreadsheet software is important. Strong time management, focus, and effective communication skills help you meet deadlines and collaborate with remote teams. These abilities are crucial to ensure high-quality, consistent data labelling that directly impacts the performance of machine learning models.
More about Virtual Data Labelling jobs
What cities are hiring for Virtual Data Labelling jobs? Cities with the most Virtual Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Virtual Data Labelling jobs? States with the most job openings for Virtual Data Labelling jobs include:
What job categories do people searching Virtual Data Labelling jobs look for? The top searched job categories for Virtual Data Labelling jobs are:
Virtual Data Labelling jobs near you
Tableau Data Architect

Tableau Data Architect

Buyers Edge Platform, LLC

Waltham, MA • Remote

$68.75 - $88.50/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

Job description

We're seeking a Tableau Data Architect to design and optimize the data architecture that powers our enterprise analytics ecosystem. This role is responsible for architecting scalable, governed, and high-performing Tableau data models that enable actionable insights across our business. You'll partner closely with data engineering, analytics, and business stakeholders to ensure that our Tableau Cloud environment delivers consistent, trusted, and performant reporting and analytics at scale including leveraging the full capabilities of Tableau Next and its AI-powered features.

This is a hands-on, strategic role for someone who can bridge the gap between data engineering and business intelligence strategy building systems that empower both analysts and executives.

Who we are:

Buyers Edge Platform is a leading digital procurement network and solutions provider for the foodservice industry, delivering savings, insights, and technology that help operators, distributors, and manufacturers succeed. Through its portfolio of solutions—including Digital Procurement Network, Fresh Services, Software Solutions, and Supply Chain Management—Buyers Edge is reshaping how the foodservice industry connects and thrives. At the heart of our work is a culture built on a passion for collaboration, technology, and helping foodservice business succeed.

We are unable to offer sponsorship for this role.

Your impact:

Data Governance & Quality
  • Own the enterprise data governance framework within Tableau Cloud, including data source certification workflows, Tableau Catalog configuration (lineage tracking, data quality warnings, sensitivity labels), metric governance via Tableau Pulse, and enforcement of naming conventions, access controls, and content promotion policies.
  • Implement and manage row-level security, object-level security, and Virtual Connection-level entitlements to centralize and enforce data access controls.
  • Leverage the Platform Data API to build automated audit trails, activity monitoring pipelines, and compliance dashboards for ongoing governance observability.
  • Partner with BI to maintain a single source of truth for KPIs and metrics across the organization.

Tableau Next & AI-Ready Architecture

  • Lead the design and governance of the semantic data model to support Tableau Next AI features, including Tableau Pulse and Einstein Copilot, ensuring metric definitions are trusted, consistent, and AI-ready.
  • Own Tableau Pulse metric definitions - defining, certifying, and deprecating official metrics organization-wide.
  • Guide governance and quality standards for AI-generated content to ensure outputs align with the organization's trusted data standards.

Architect and Design Tableau Data Models

  • Develop optimized semantic layers and certified data sources for Tableau dashboards and analytics.
  • Implement best practices for star schema design, LOD calculations, and data blending.
  • Design and manage Virtual Connections and published data sources to centralize data access and enforce governance at the connection layer.

Performance Optimization

  • Diagnose and tune underperforming dashboards using Tableau Performance Recorder, database query analysis, and Admin Insights dashboards for site-wide performance monitoring.
  • Work closely with engineering to optimize SQL, indexing, and extract strategies. Integration, Automation and Pipeline Monitoring
  • Collaborate with other departments to integrate Tableau Cloud with upstream systems (e.g., Salesforce, Redshift).
  • Partner closely with Data Engineering to monitor data pipeline health, implement validation checks across databases and Tableau data sources, and proactively identify syncing issues or failures before they impact downstream reporting.
  • Drive transparency across data source connections by communicating pipeline issues, failures, and potential downstream effects to impacted stakeholders in a timely manner
  • Automate extract refreshes, data source updates, and quality monitoring.
  • Utilize the Tableau REST API and Metadata API for governance automation, bulk permission management, content migration, lineage auditing, and user provisioning.
  • Utilize the VizQL Data Service to expose governed published data sources to downstream applications and automated workflows.
  • Leverage the Platform Data API for activity monitoring, audit log ingestion, and governance reporting.
Leadership & Enablement
  • Guide BI developers and analysts on Tableau best practices and reusable data design.
  • Partner with business stakeholders to translate KPIs and reporting needs into technical solutions.
  • Help define and evolve the company's enterprise BI strategy.

About you:

  • 4+ years of experience in business intelligence, data architecture, or analytics engineering, with at least 3 years focused on Tableau.
  • Expert-level proficiency in Tableau Cloud, including site administration, performance tuning, governance, and LOD expressions.
  • Deep experience with Tableau data governance: Tableau Catalog, certified data sources, Virtual Connections, row-level and object-level security.
  • Proficiency with the Tableau REST API for governance automation workflows and the Tableau Metadata API (GraphQL) for lineage and catalog querying.
  • Advanced SQL skills (preferably Amazon Redshift).
  • Strong understanding of data modeling, star/snowflake schema, and semantic layer design.
  • Experience integrating Tableau with large-scale data ecosystems (ETL pipelines, APIs, or cloud data storage).
  • Knowledge of data governance, metadata management, and security principles.
  • Familiarity with the Platform Data API for activity monitoring and audit log ingestion.
  • Proven ability to collaborate with both technical and non-technical stakeholders.
  • Excellent communication skills, with a proactive approach to sharing updates on progress, timelines, and roadblocks along with proposed solutions.

Education and Experience:

  • Hands-on experience with Tableau Next features including Tableau Pulse metric configuration and Einstein Copilot.
  • Experience with the VizQL Data Service for programmatic access to published data sources.
  • Familiarity with Tableau Cloud Admin Insights for site-wide usage and performance analytics.
  • Experience with Amazon Redshift.
  • Familiarity with Salesforce integrations.
  • Python scripting experience, including use of the Tableau Server Client (TSC) library or VizQL Data Service Python SDK for automation.
  • Prior experience in a high-growth, data-driven organization.

Not sure you meet every qualification? Studies show that diverse applicants often hesitate to apply unless they check every box. At Buyers Edge Platform, we value authenticity and inclusion—if you're excited about the role, we encourage you to apply. You might be exactly who we're looking for!

What's in this for you:

  • Great benefits from day one. We offer medical, dental, vision, FSA, company-paid life insurance, and more—plus a 401(k) with company match.
  • Grow with us. Enjoy strong training, development, and competitive pay.
  • Work-life balance. Our flexible PTO policy lets you take time when you need it—no accrual required.

We welcome all.

We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth and pregnancy-related conditions), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other characteristic protected by applicable federal, state or local laws and ordinances.