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Ai Data Annotation Remote Jobs in Missouri (NOW HIRING)

Jobgether

$88K - $106K/yr

This is a remote opportunity for an experienced data engineer to play a key role in a large-scale ... Leverage AI-powered tools where appropriate for code generation, data analysis, automation ...

Jobgether

$88K - $106K/yr

You will have opportunities to apply AI-assisted tools to accelerate development, testing ... Install, configure, monitor, and troubleshoot Talend Remote Engine environments while maintaining ...

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Ai Data Annotation Remote information

What is an AI data annotation remote?

An AI Data Annotation Remote job involves labeling, tagging, or categorizing data used to train artificial intelligence models. Annotators work with text, images, audio, or video to ensure machine learning algorithms receive accurate and high-quality input. This role is performed remotely, allowing flexibility in work location and schedule. Attention to detail, consistency, and familiarity with annotation tools are essential skills for this job.

What does a typical day look like for someone working remotely in AI data annotation?

A typical day for a remote AI Data Annotation worker involves reviewing and labeling various types of data such as images, text, or audio according to specific guidelines provided by the employer or project lead. You may use specialized annotation software and work through batches of data while following quality standards and deadlines. Periodic team check-ins or virtual meetings help clarify instructions, address questions, and monitor progress. While most of the work is independent, communication with supervisors or quality assurance teams is important to ensure that data labeling is consistent and accurate.

What are the key skills and qualifications needed to thrive in the AI data annotation remote position, and why are they important?

To thrive as an AI Data Annotation Remote worker, you need strong attention to detail, familiarity with data labeling processes, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant experience. Familiarity with data annotation platforms such as Labelbox, Supervisely, or AWS SageMaker Ground Truth is typically required, and certifications in data annotation or AI may be advantageous. Strong time management, the ability to work independently, and clear communication skills are valuable in this remote role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable AI models.

What are the most commonly searched types of Ai Data Annotation jobs in Missouri?

The most popular types of Ai Data Annotation jobs in Missouri are:

What are popular job titles related to Ai Data Annotation Remote jobs in Missouri?

For Ai Data Annotation Remote jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Ai Data Annotation Remote jobs in Missouri look for?

The top searched job categories for Ai Data Annotation Remote jobs in Missouri are:

What cities in Missouri are hiring for Ai Data Annotation Remote jobs?

Cities in Missouri with the most Ai Data Annotation Remote job openings:

Ai Data Annotation Remote jobs near you
Infographic showing various Ai Data Annotation Remote job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Data Engineer - Senior

Jobgether

Remote

$88K - $106K/yr

Contractor

Posted 10 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer - Senior based in Netherlands.

This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions that support reliable, analytics-ready information across the organization. Working closely with business stakeholders, product owners, architects, and technical teams, you will help turn diverse data sources into trusted and usable datasets. The role has a strong focus on the Microsoft Azure data ecosystem and modern cloud-based data architectures. You will work extensively with Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2, Python, SQL, and Delta Lake. This is an environment where strong engineering practices, problem-solving, and data quality directly contribute to business and technology outcomes.

Accountabilities
  • Design, develop, and maintain scalable, reliable data solutions supporting a large-scale digital transformation program.
  • Build and optimize robust ETL/ELT pipelines that integrate data from diverse sources into trusted, analytics-ready datasets.
  • Develop cloud-based data solutions using the Microsoft Azure ecosystem, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL, and related services.
  • Use Python and SQL to develop data transformations, processing workflows, integrations, and analytical data solutions.
  • Design and manage data models and architectures that support scalability, reliability, performance, and data quality.
  • Work extensively with Azure Databricks and Delta Lake to build and optimize modern data processing and storage solutions.
  • Collaborate with business stakeholders, product owners, data architects, and technical teams to understand requirements and translate them into effective data engineering solutions.
  • Apply version control and engineering best practices using tools such as Git to support maintainable, collaborative development.
  • Leverage AI-powered tools where appropriate for code generation, data analysis, automation, optimization, and other data engineering activities.
  • Troubleshoot technical issues, optimize data workflows, and continuously improve pipeline performance, reliability, and maintainability.
  • Communicate technical concepts clearly and contribute to effective collaboration across business and technical teams.
Requirements:
  • At least 5 years of hands-on experience with Python and SQL in a data engineering environment.
  • At least 3 years of experience working with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
  • At least 3 years of hands-on experience with Azure Databricks and Delta Lake.
  • At least 3 years of experience designing data solutions and developing trusted, analytics-ready datasets.
  • At least 4 years of experience with version control systems, particularly Git.
  • At least 1 year of practical experience using AI tools for code generation, data analysis, automation, optimization, or related data engineering tasks.
  • Strong understanding of data engineering principles, ETL/ELT processes, data integration, and data pipeline development.
  • Advanced SQL development and data transformation capabilities.
  • Proven experience working with cloud-based data platforms and modern data architectures.
  • Strong analytical and problem-solving abilities, with a structured approach to diagnosing and resolving complex technical challenges.
  • Excellent communication and collaboration skills, with the ability to work effectively with both technical teams and business stakeholders.
  • Ability to work independently in a remote environment while maintaining strong ownership, organization, and delivery focus.
Benefits:
  • Fully remote position, offering flexibility to work from Slovenia.
  • Opportunity to contribute to a large-scale digital transformation initiative with significant data engineering scope.
  • Work with a modern Microsoft Azure cloud data ecosystem and widely used data engineering technologies.
  • Exposure to advanced platforms and tools including Azure Databricks, Delta Lake, Azure Synapse, Azure Data Factory, Python, and SQL.
  • Opportunity to apply AI-powered engineering tools to improve development, automation, analysis, and optimization.
  • Collaboration with multidisciplinary teams including business stakeholders, product owners, data architects, and technical specialists.
  • Opportunity to work on scalable, production-focused data solutions with direct business impact.
  • Remote working environment designed to support autonomy and flexibility.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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