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Part Time Data Engineering Jobs in Oklahoma (NOW HIRING)

Engineer (Part-Time)

Tulsa, OK · On-site

$15 - $17/hr

Engineer, Role Specific Duties and Expectations Other Duties and Expectations * Repair Requests ... Respond to emergency situations using information contained in Material Safety Data sheets. * Full ...

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Part Time Data Engineering information

What are the key skills and qualifications needed to thrive as a Part Time Data Engineer, and why are they important?

To thrive as a Part Time Data Engineer, you need proficiency in programming languages like Python or SQL, knowledge of database management, and a degree in computer science or a related field. Familiarity with data warehousing tools, ETL processes, and platforms such as AWS, Google Cloud, or Apache Spark is typically required. Strong problem-solving abilities, attention to detail, and effective communication help individuals excel in this flexible role. These skills ensure accurate data pipelines, efficient data processing, and successful collaboration with cross-functional teams, even in a part-time capacity.

What is a part-time data engineering job?

A part-time data engineering job involves working fewer hours than a full-time position, typically focusing on building and managing data pipelines, organizing data storage, and ensuring data quality for organizations. Part-time data engineers may work on specific projects or provide support to larger teams, often with flexible schedules. They use programming languages and tools like Python, SQL, and cloud platforms to move, transform, and optimize data. This role is ideal for those seeking work-life balance, students, or professionals looking to gain experience or supplement their income.

How does a part-time data engineering role typically balance project responsibilities with limited working hours?

In a part-time data engineering position, tasks are often scoped to fit within your available hours, focusing on specific projects or maintenance work rather than broader, ongoing initiatives. You’ll likely collaborate closely with full-time engineers to ensure hand-offs are smooth and that you’re aligned on priorities. Clear communication and proactive time management are essential, as you may need to coordinate across teams or adjust your workload to meet deadlines. Many organizations also provide flexible scheduling and clear documentation practices to help part-time team members stay integrated and productive.

What is the difference between Part Time Data Engineering vs Part Time Data Analysis?

AspectPart Time Data EngineeringPart Time Data Analysis
Required CredentialsTypically requires knowledge of SQL, Python, ETL tools, and cloud platformsRequires skills in SQL, Excel, data visualization tools, and basic statistical knowledge
Work EnvironmentOften involves building data pipelines, managing databases, and working with data infrastructureFocuses on interpreting data, creating reports, and providing insights
Employer & Industry UsageUsed in tech companies, finance, and e-commerce for data infrastructure rolesCommon in marketing, consulting, and business intelligence roles across industries

Part Time Data Engineering involves developing and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. In contrast, Part Time Data Analysis centers on interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but differ in technical complexity and focus.

What are the most commonly searched types of Data Engineering jobs in Oklahoma? The most popular types of Data Engineering jobs in Oklahoma are:
Infographic showing various Part Time Data Engineering job openings in Oklahoma as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 10% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

AI Flight Optimization Engineering Intern

Skydweller US

Oklahoma City, OK • On-site

$15.50 - $20/hr

Part-time, Internship

Posted 12 days ago


Job description

About Skydweller
Skydweller is developing the world's largest autonomous solar-powered aircraft, designed to provide persistent, long-duration flight capabilities for defense, and commercial missions. Our aircraft combines advanced aerospace engineering, autonomy, renewable energy technologies, and artificial intelligence to enable next-generation aviation capabilities.
Skydweller's engineering and flight-test programs generate significant volumes of aircraft telemetry, environmental data, and mission information. We are applying emerging AI technologies to transform this data into actionable insights that improve aircraft performance, operational efficiency, and mission planning.
About the Role
Skydweller is seeking an intern to support the development of an Agentic AI system dedicated to flight operations and optimization for long-endurance unmanned aircraft systems (UAS).
The intern will work alongside experienced aerospace, software, and AI engineers to design and prototype an Agentic AI system capable of analyzing flight-test telemetry, weather data, and mission constraints to generate recommendations that improve endurance, energy efficiency, and aircraft performance.
The intern will participate in a structured, mentored R&D experience progressing from AI fundamentals through implementation and validation of a functional prototype supporting Skydweller's flight optimization efforts.
Why Join Skydweller?
This internship provides a unique opportunity to work on advanced aerospace technology while helping define the future of AI-assisted engineering.
Unlike traditional AI projects focused on generic applications, this role applies emerging AI technologies to a real-world autonomous aircraft program. The intern will contribute directly to the development of tools that improve aircraft endurance, mission effectiveness, and engineering decision-making.
Successful candidates will gain experience at the intersection of artificial intelligence, aerospace engineering, and autonomous systems, while working with an experienced team developing next-generation aviation capabilities.
Student Requirements
  • Interns must be currently enrolled undergraduate or graduate students at an Oklahoma college/university, or CareerTech students concurrently enrolled in college-level coursework
  • Due to the nature of the work, the intern needs to be a U.S. Person (US Citizen/Green Card holder)

Qualifications
  • Graduate or upper-level undergraduate student in Computer Science, Aerospace Engineering, or related field
  • Proven experience with Python programming
  • Prior participation in R&D projects, especially in the fields of AI-agent, Aerospace, or Meteorology, is a plus
  • Familiarity with AI/ML concepts (LLMs, Deep Learning, etc.), or data processing preferred

Responsibilities
The AI Flight Optimization Engineering Intern will serve in a junior, mentored software development role within Skydweller's Research & Development environment. Responsibilities include:
  • Develop Python-based tools and AI workflows using modern software development practices and Git version control
  • Assist with data preparation, system testing, and validation activities
  • Document code, workflows, system architecture, and write activity reports
  • Participate in agile development cycles, design reviews, and technical discussions

Learning Experience
During the internship, the candidate will gain practical experience in:
  • Artificial intelligence and machine learning applications for aerospace systems
  • Agentic AI architectures and AI-enabled engineering workflows
  • Processing and analysis of aerospace telemetry datasets
  • Software development in a production-oriented aerospace environment
  • Autonomous aircraft operations and flight optimization concepts

Work Environment
This is a part-time 1-year internship onsite at the Skydweller Oklahoma City (OKC) Office. The role integrates the intern directly into active aerospace R&D workflows, providing exposure to advanced autonomous systems development and collaboration with AI and engineering teams.