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Entry Level Ai Data Engineer Jobs in Oklahoma (NOW HIRING)

Addison Group

Sr. Data Engineer

Oklahoma City, OK · On-site

$50 - $70/hr

Leverage AI-assisted development and emerging technologies to improve data engineering and analytical capabilities. Qualifications: * Senior-level experience in data engineering, data analytics ...

Pwc

Data Engineer - Senior Associate

Oklahoma City, OK · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

Data Engineer - Senior Associate

Tulsa, OK · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

System One

AI Systems Engineer

Tulsa, OK · On-site

Help organize, structure, and optimize operation data for AI usage * Assist with improving and ... Strong programming experience with Python and backend development concepts * Familiarity with ...

System One

AI Systems Engineer

Tulsa, OK · On-site

Help organize, structure, and optimize operation data for AI usage * Assist with improving and ... Strong programming experience with Python and backend development concepts * Familiarity with ...

New

Pwc

US Tech - AI Engineering Senior Associate

Tulsa, OK · On-site

$55K - $187K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Uofl

$185K/yr

Master's degree or higher in Computer Engineering, Computer Science, or Data Science and two (2) years of relevant experience. Grade 13 (Salaried) Position Description: The position of Senior AI ...

Uofl

$185K/yr

Master's degree or higher in Computer Engineering, Computer Science, or Data Science and two (2) ... The role translates frontier AI into deployable systems across clinical imaging pipelines ...

Uofl

$185K/yr

Master's degree or higher in Computer Engineering, Computer Science, or Data Science and two (2) ... The University of Louisville is seeking a Senior AI Engineer to lead the design and delivery of ...

ONEOK, Inc.

AI Analyst

Tulsa, OK · On-site

$92 - $138/hr

## AI AnalystApplylocations: Tulsa, OK: Dallas, TXtime type: Full timeposted on: Posted Todayjob ... Minimum 3 years in an analytical role (e.g., operations analyst, data analyst, process engineer ...

Oneok, Inc.

AI Analyst

Tulsa, OK · On-site

The AI Analyst combines AI tooling with operations domain expertise to provide decision support ... Minimum 3 years in an analytical role (e.g., operations analyst, data analyst, process engineer ...

ONEOK, Inc

AI Analyst

Tulsa, OK · On-site

The AI Analyst combines AI tooling with operations domain expertise to provide decision support ... Minimum 3 years in an analytical role (e.g., operations analyst, data analyst, process engineer ...

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Entry Level Ai Data Engineer information

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, understand data pipelines and databases, and gain experience with cloud platforms such as AWS or Azure. Completing relevant certifications or courses in data engineering and machine learning can also improve job prospects.

What are the most commonly searched types of Ai Data Engineer jobs in Oklahoma?

The most popular types of Ai Data Engineer jobs in Oklahoma are:

What are popular job titles related to Entry Level Ai Data Engineer jobs in Oklahoma?

For Entry Level Ai Data Engineer jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Engineer jobs in Oklahoma look for?

The top searched job categories for Entry Level Ai Data Engineer jobs in Oklahoma are:

Entry Level Ai Data Engineer jobs near you
Infographic showing various Entry Level Ai Data Engineer job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Sr. Data Engineer

Addison Group

Oklahoma City, OK • On-site

$50 - $70/hr

Contractor

Medical, Dental, Vision, Retirement

Posted 5 days ago

Job description

Job Title: Senior Data Engineer
Location: Oklahoma City, OK
Pay: $50 - $70 / Hour
Work Schedule: Hybrid - 4 days onsite and 1 day remote initially
Benefits: This position is eligible for medical, dental, vision, and 401(k).
About The Company:
A well-established organization in the energy and utilities industry is seeking a Senior Data Engineer to join its analytics team. This is an opportunity to work on meaningful, high-impact data initiatives that influence operational performance, reliability, risk management, and business decision-making.
Job Description:
The Senior Data Engineer will design, develop, and support data solutions that transform complex operational information into reliable, actionable insights. This individual will work across data engineering, business intelligence, statistical analysis, and emerging AI technologies.
A key focus of the role will be analyzing data related to reliability and vegetation management programs, evaluating the impact of operational changes, and developing analytics that help stakeholders understand performance, risk, customer impact, and opportunities for improvement.
The ideal candidate is an experienced data professional who can work independently, solve complex problems, and translate ambiguous business questions into practical technical solutions.
Key Responsibilities:
  • Build and maintain scalable data pipelines, analytical datasets, and reporting solutions.
  • Write and optimize SQL queries while investigating data quality and transformation issues.
  • Develop Power BI dashboards, reports, semantic models, and other business intelligence solutions.
  • Work with data from multiple enterprise systems and sources to create comprehensive analytical views.
  • Perform statistical analysis to measure operational performance and determine the effectiveness of business initiatives.
  • Analyze reliability, outage, asset, vegetation, customer, and operational data to identify trends and potential risks.
  • Develop meaningful performance indicators and analytical models that supplement traditional reliability measurements.
  • Create dashboards, scorecards, rankings, and visualizations that help business leaders prioritize actions.
  • Validate data, reconcile discrepancies between systems, and document assumptions and business logic.
  • Translate business needs into repeatable data models, analytical processes, and user-friendly solutions.
  • Support production data environments through troubleshooting, quality checks, version control, and ongoing improvements.
  • Collaborate with technical teams and business stakeholders to gather requirements and deliver effective solutions.
  • Leverage AI-assisted development and emerging technologies to improve data engineering and analytical capabilities.

Qualifications:
  • Senior-level experience in data engineering, data analytics, business intelligence, or a related field.
  • Strong SQL development and data troubleshooting experience.
  • Experience with ETL/ELT processes and data pipeline development.
  • Experience with Power BI and/or Microsoft Fabric.
  • Knowledge of data modeling and modern enterprise data environments.
  • Ability to use AI tools or prompting techniques to assist with programming and data-related tasks.
  • Strong analytical, problem-solving, and critical-thinking skills.
  • Ability to independently research, investigate, and resolve complex data challenges.
  • Excellent communication skills with both technical and non-technical audiences.
  • Strong attention to detail and commitment to data accuracy.
  • Self-motivated with the ability to work effectively with limited supervision.

Preferred Qualifications:
  • Experience with Minitab Statistical Software or a similar statistical analysis platform.
  • Experience with Snowflake and enterprise data warehousing.
  • Experience with Microsoft Fabric, Lakehouse environments, or cloud-based data solutions.
  • Experience working with SAP or other large enterprise systems.
  • Experience with GIS or geospatial data.
  • Utility, energy, infrastructure, engineering, or other asset-intensive industry experience.
  • Knowledge of electric reliability concepts and operational performance metrics.
  • Experience developing predictive, leading, or customer-focused reliability indicators.
  • Familiarity with AI platforms, machine learning, predictive analytics, or intelligent automation.

Additional Details:
  • This position is structured as contract-to-hire, with the potential for permanent employment based on business needs and performance.
  • The initial schedule is expected to be 4 days onsite and 1 day remote. Additional remote flexibility may become available after approximately six months but is not guaranteed.
  • The anticipated start date is October 2026, with potential flexibility for an earlier start.
  • The interview process includes two interviews and a practical data exercise.
  • Candidates should be prepared to demonstrate their technical, analytical, and problem-solving abilities.
  • This is a senior-level position, and the selected candidate is expected to be productive with minimal training.

Perks:
  • Work on high-impact data initiatives with measurable business and operational outcomes.
  • Opportunity to work across data engineering, analytics, statistics, and emerging AI technologies.
  • Exposure to modern data platforms and enterprise analytics environments.
  • Potential pathway from contract to permanent employment.
  • Hybrid work flexibility.
  • Opportunity to directly influence reliability, operational performance, and strategic decision-making.

Addison Group is an Equal Opportunity Employer. Addison Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. Addison Group complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. Reasonable accommodation is available for qualified individuals with disabilities, upon request.
IND 005-010

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