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Full Time Remote Data Engineer Jobs in Missouri (NOW HIRING)

$5.0K - $6.5K/mo

This fully remote opportunity is designed for an experienced Python engineer passionate about building scalable data platforms and solving complex backend challenges. In this role, you will ...

$66K - $83K/yr

  • PTO

You will work closely with Product, Game Operations, Marketing, CRM, Engineering, and other cross ... Remote-first working environment. * Competitive salary with individual performance-based bonuses ...

Software Engineer

Saint Louis, MO · On-site +1

$100K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Software Engineer (Azure Cloud, Data Engineering & Automation) | Hybrid - St. Louis, MO We are ... driven workflow (shell, remote access and debugging) on macOS or Linux. Preferred Skills ...

Software Engineer

Saint Louis, MO · On-site +1

$100K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Software Engineer (Azure Cloud, Data Engineering & Automation) | Hybrid - St. Louis, MO We are ... driven workflow (shell, remote access and debugging) on macOS or Linux. Preferred Skills ...

Software Engineer

Saint Louis, MO · On-site +1

$100K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Software Engineer (Azure Cloud, Data Engineering & Automation) | Hybrid - St. Louis, MO We are ... Working environment: comfortable in a CLI-driven workflow (shell, remote access and debugging) on ...

Software Engineer

Saint Louis, MO · On-site +1

$100K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Software Engineer (Azure Cloud, Data Engineering & Automation) | Hybrid - St. Louis, MO We are ... Working environment: comfortable in a CLI-driven workflow (shell, remote access and debugging) on ...

Fri remote) for candidates in the Kansas City area and open to qualified remote candidates outside ... Work closely with data engineering, data science, data governance, and platform teams to develop ...

Software Engineer

Saint Louis, MO · On-site +1

$100K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Software Engineer (Azure Cloud, Data Engineering & Automation) | Hybrid - St. Louis, MO We are ... Working environment: comfortable in a CLI-driven workflow (shell, remote access and debugging) on ...

$94K - $124K/yr

... data-driven products using cutting-edge ML techniques, remote sensing data, and geospatial ... This is an ideal opportunity for an experienced engineer passionate about applying AI to create ...

  • Medical

  • Retirement

  • PTO

Working across data engineering, backend development, and personalization, you will design systems ... Benefits * 100% remote work with flexible working hours and designated core collaboration hours.

$66K - $83K/yr

... data engineering, delivering insights that shape decision-making and support large-scale ... Working in a fully remote, international environment, you will contribute to high-impact projects ...

This full-time remote role offers the opportunity to create visually engaging content across ... Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process ...

Database Engineer - Remote

Rolla, MO · On-site +1

$70K - $80K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Database Engineer (Remote) As a Database Engineer, you will help design, support, and optimize the data systems that power critical environmental research for the U.S. Geological Survey (USGS). In ...

Showing results 21-40

Full Time Remote Data Engineer information

What does a full time remote data engineer do?

A Full Time Remote Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and databases from a remote location. They work with large sets of data, ensuring it is collected, stored, and processed efficiently for analysis and business decision-making. These engineers collaborate with data scientists, analysts, and other stakeholders to provide reliable data infrastructure while using tools such as SQL, Python, and cloud platforms. Working remotely, they leverage communication tools and version control systems to stay connected with their teams and manage projects effectively.

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

To thrive as a Full Time Remote Data Engineer, you need strong programming skills (such as Python or Scala), a solid understanding of data modeling, and experience with database systems, often supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and relevant certifications (e.g., Google Cloud Professional Data Engineer) is typically required. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive. These competencies ensure robust, scalable data solutions and seamless teamwork across distributed environments.

How do full time remote data engineers typically collaborate with cross-functional teams while working remotely?

Full Time Remote Data Engineers often work closely with data scientists, analysts, and software developers through virtual collaboration tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular stand-up meetings, sprint planning sessions, and code reviews are common practices to ensure alignment and smooth workflow across different time zones. Clear documentation, proactive communication, and sharing progress updates are essential for overcoming the challenges of remote teamwork and ensuring project goals are met efficiently.

What is the difference between Full Time Remote Data Engineer vs Full Time Remote Data Analyst?

AspectFull Time Remote Data EngineerFull Time Remote Data Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certifications (e.g., Google Cloud Professional Data Engineer)Bachelor's in Statistics, Data Analysis certifications (e.g., Microsoft Certified Data Analyst)
Work EnvironmentDesigning data pipelines, managing databases, coding in Python, SQL, cloud platformsInterpreting data, creating reports, visualizations, using Excel, Tableau, SQL
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing firms, consulting, finance, retail

Full Time Remote Data Engineers focus on building and maintaining data infrastructure, requiring technical skills in programming and cloud platforms. Data Analysts interpret data and create insights, often using visualization tools. Both roles are in high demand for remote work, but they serve different functions within organizations.

What are the most commonly searched types of Remote Data Engineer jobs in Missouri?

The most popular types of Remote Data Engineer jobs in Missouri are:

Infographic showing various Full Time Remote Data Engineer job openings in Missouri as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Sr AI Engineer / Data Scientist

Koantek

Chesterfield, MO • Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Location: United States – Remote
Employment Type: Full-Time and Contract


We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities

●       Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions.

●       Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences.

●       Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models.

●       Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.

●       Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems.

●       Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark).

●       Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities.

●       Ensure all client engagements and training activities are properly documented and reported via designated partner platforms.

Required Qualifications

●       4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment.

●       3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

●       Excellent verbal and written communication skills for effective client and internal team interaction.

●       Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.

●       Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

●       Deep understanding of programming for data-intensive and scalable ML applications.

●       Proven experience in deploying and managing Generative AI and NLP solutions for client applications.

Preferred Qualifications

●       Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

●       Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.

●       Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

 


Requirements

●       Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

●       Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.

●       Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.
Requirements

Required Qualifications

●       4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment.

●       3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

●       Excellent verbal and written communication skills for effective client and internal team interaction.

●       Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.

●       Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

●       Deep understanding of programming for data-intensive and scalable ML applications.

●       Proven experience in deploying and managing Generative AI and NLP solutions for client applications.

Preferred Qualifications

●       Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

●       Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.

●       Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

 

Requirements


●       Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

●       Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing.

●       Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.


Benefits
  • Work on frontier AI and data projects with Fortune 500 companies

  • Contribute to IP, reusable accelerators, and real business impact

  • Be part of a high-performance, engineering-first culture