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Remote Ai Data Engineer Jobs in Georgetown, TX (NOW HIRING)

3B Staffing LLC

Data Engineer

Austin, TX · Remote

$113K - $136K/yr

Data Engineer - Cloud Infrastructure (BigQuery, Python, Terraform) Summary: We are seeking a highly ... Remote * Duration: Long-term contract (12+ months) * Client: Major technology client

3B Staffing LLC

Data Engineer

Austin, TX · Remote

$113K - $136K/yr

Data Engineer - Cloud Infrastructure (BigQuery, Python, Terraform) Summary: We are seeking a highly ... Remote * Duration: Long-term contract (12+ months) * Client: Major technology client

Cloudelligent

AWS Solutions Architect- AI/ML

Austin, TX · Remote

$64.25 - $84.25/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with ... You will focus on cloud modernization, data engineering, and AI/ML integration to drive business ...

Loxo

Data Engineer

Austin, TX · On-site +1

$113K - $136K/yr

As an early hire to our engineering team, you will be responsible for managing Loxo's data ... Progressive culture * 100% flexibility in living and working from anywhere you want * 100% remote ...

VetsEZ

Data Engineer (Remote Opportunity)

Austin, TX · On-site +1

$113K - $136K/yr

We are currently looking for a Data Engineer for a 100% remote position on a large federal government project. This role focuses on designing, developing, and maintaining scalable data solutions that ...

VetsEZ

Data Engineer (Remote Opportunity)

Austin, TX · On-site +1

$113K - $136K/yr

We are currently looking for a Data Engineer for a 100% remote position on a large federal government project. This role focuses on designing, developing, and maintaining scalable data solutions that ...

ServiceNow

Solution Architect - AI & Data

Austin, TX · On-site +1

$62.50 - $82.25/hr

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

Virtasant

Senior Data Engineer, Data Platform

Austin, TX · On-site +1

$113K - $136K/yr

About the role We're looking for a Senior Data Engineer to join us and work with our client's Data ... Totally remote within the contiguous United States, full-time (40h/week) * Stable, long-term ...

TEXAS RESEARCH INTERNATIONAL INC

Cloud Data Engineer

Austin, TX · Remote

$55.25 - $73.75/hr

Open for Remote We are aggressively hiring Cloud Data Engineers with excellent background in Data Engineering and architecture. We need someone with strong Microsoft Cloud experience, including Azure ...

Citizens Bank

Principal Data Engineer - Neo4J

Austin, TX · On-site +1

Principal Data Engineer - Graph Data Engineering Neo4j Role Summary As Principal Data Engineer, you ... Familiarity with machine learning and AI techniques leveraging graph data * Experience working in ...

Virtasant

Senior Data Engineer, Data Platform

Austin, TX · Remote

$113K - $136K/yr

About the role We're looking for a Senior Data Engineer to join us and work with our client's Data ... Totally remote within the contiguous United States, full-time (40h/week) * Stable, long-term ...

YO AI Labs

AI Engineer - Remote

Austin, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

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All JobsAi Data Engineer JobsRemote Ai Data Engineer JobsRemote Ai Data Engineer Jobs in Georgetown, TX

Remote Ai Data Engineer information

See Georgetown, TX salary details

$41.3K

$120.5K

$164.9K

How much do remote ai data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote ai data engineer in Georgetown, TX is $120,522.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,400.00 and $127,800.00 per year, depending on experience, location, and employer.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

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

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What are popular job titles related to Remote Ai Data Engineer jobs in Georgetown, TX?

For Remote Ai Data Engineer jobs in Georgetown, TX, the most frequently searched job titles are:

What job categories do people searching Remote Ai Data Engineer jobs in Georgetown, TX look for?

The top searched job categories for Remote Ai Data Engineer jobs in Georgetown, TX are:

What cities near Georgetown, TX are hiring for Remote Ai Data Engineer jobs?

Cities near Georgetown, TX with the most Remote Ai Data Engineer job openings:

Remote Ai Data Engineer jobs near you

Data Engineer

3B Staffing LLC

Austin, TX • Remote

$113K - $136K/yr

Full-time

Posted 10 days ago

Job description

Data Engineer - Cloud Infrastructure (BigQuery, Python, Terraform) Summary: We are seeking a highly skilled Data Engineer with hands-on experience in BigQuery, Python, SQL, and Terraform to help modernize and optimize our cloud data infrastructure. This role will focus on building efficient, scalable, and cost-effective data environments across GCP and AWS. The ideal candidate is technically strong, detail-oriented, and a proactive collaborator who communicates effectively across engineering, data, and finance teams. This individual should be passionate about automation, cloud optimization, and continuous improvement within modern data ecosystems. Key Responsibilities:

  • Redesign and optimize BigQuery environments for improved scalability, performance, and cost efficiency.
  • Build and maintain ETL/ELT pipelines using Python, SQL, Terraform, and Git-based workflows, ensuring reliable data delivery from development to production.
  • Apply FinOps practices to monitor, analyze, and optimize cloud data costs across AWS and GCP environments.
  • Collaborate with Financial Analysts and data stakeholders to structure, import, and manage large datasets in a scalable and governed way.
  • Implement and enforce data quality, validation, and governance frameworks to ensure data accuracy and consistency.
  • Automate workflows and identify opportunities to enhance efficiency in data operations and infrastructure management.
  • Partner with cross-functional teams (engineering, operations, analytics, and business units) to align on architecture, deployment strategies, and best practices.
  • Communicate clearly and proactively, providing updates, documentation, and insights to both technical and non-technical audiences.
  • Contribute to team knowledge sharing and continuous improvement, supporting a culture of collaboration and innovation. Required Skills &

Qualifications:

  • 4+ years of experience in data engineering, cloud infrastructure, or similar roles.
  • Strong proficiency in SQL and Python, with experience in automation, data transformation, and pipeline development.
  • Hands-on experience with BigQuery, data lakes, and data warehousing design.
  • Experience with Terraform, CI/CD tools (GitLab, Jenkins, etc.), and infrastructure-as-code workflows.
  • Familiarity with FinOps concepts, including cost monitoring, optimization, and budgeting for cloud resources.
  • Working knowledge of AWS and GCP services (Lambda, Cloud Functions, Compute, etc.).
  • Excellent communication and teamwork skills, with the ability to collaborate effectively in cross-functional environments.
  • Strong problem-solving, analytical, and documentation abilities, with a focus on delivering measurable impact. Other

Details:

  • Location: Remote
  • Duration: Long-term contract (12+ months)
  • Client: Major technology client

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