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Data Modeling Jobs in Oklahoma (NOW HIRING)

Staff Data Engineer

Oklahoma City, OK ยท On-site

$140 - $200/hr

Solid understanding of data modeling, data warehousing concepts, and distributed data processing7. Experience working with cloud platforms (Azure, AWS, or GCP) and cloud-native data services8.

... data modeling, and system optimization. This is an execution-focused role responsible for building, maintaining, and improving reporting outputs and underlying data structures. The position ...

Tulsa, OK Job Type: Full Time * Develops, implements, and supports business intelligence reporting and advanced * analytical model development, architecture, data availability and data models

Sr. Data Engineer

Oklahoma City, OK ยท On-site

$50 - $70/hr

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 ...

Data Engineer

Edmond, OK ยท On-site

$125K - $150K/yr

Design, manage, and optimize data models, schemas, views, and database structures. * Support Azure SQL database administration, including performance tuning, security, access controls, and ...

Data Engineer

Edmond, OK ยท On-site

$125K - $150K/yr

Design, manage, and optimize data models, schemas, views, and database structures. * Support Azure SQL database administration, including performance tuning, security, access controls, and ...

Model and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. As part of the Data and ...

Data Engineer - Senior Manager

Tulsa, OK ยท On-site

$124K - $280K/yr

Model and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. As part of the Data and ...

As a Manager you can lead the development of data models, support compliance with data governance policies, and collaborate with business stakeholders to translate data requirements into technical ...

Performs data modeling and database design for data and reporting applications as well as other applications as needed. * Performs analysis, design, and implementation of data migration as needed.

Data Modeling and visualization experience preferred (SQL, Power BI, Spotfire, etc.) Licenses and Certifications * None required Strength Factor Rating - Physical Demands/Requirements * Sedentary ...

Strong expertise with SQL Server, Oracle, ETL development, and enterprise data modeling. * Experience with Azure, AWS, or Google Cloud data platforms. * Experience supporting ERP ecosystems such as ...

Showing results 41-60

Data Modeling information

See Oklahoma salary details

$9

$54

$76

How much do data modeling jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for data modeling in Oklahoma is $54.21, according to ZipRecruiter salary data. Most workers in this role earn between $48.61 and $63.03 per hour, depending on experience, location, and employer.

What is a data modeling?

A Data Modeling job involves designing and structuring data to ensure it is organized, efficient, and scalable for business needs. Data modelers create conceptual, logical, and physical data models that define relationships between data elements. They work closely with database administrators, data engineers, and analysts to optimize data storage and retrieval. Their role is crucial for maintaining data integrity and supporting business intelligence and analytics initiatives. Skills in SQL, database design, and data normalization are essential for success in this role.

What does a typical day look like for someone working in data modeling?

A typical day in Data Modeling often involves collaborating with business analysts, database administrators, and software developers to understand data requirements and translate them into logical and physical data structures. Data modelers spend time designing, reviewing, and optimizing data models, ensuring accuracy and consistency across systems and projects. They also review data flows, document data dictionaries, and participate in meetings to align data architecture with overall business needs. The role frequently requires balancing independent technical work with teamwork, as well as responding to feedback and evolving project requirements to support organizational goals.

What are the key skills and qualifications needed to thrive in data modeling, and why are they important?

To thrive in Data Modeling, you need strong analytical skills, proficiency in database design, and a solid understanding of data structures, usually supported by a degree in computer science, information systems, or a related field. Expertise with tools such as ERwin, SQL, PowerDesigner, or similar data modeling software, as well as knowledge of normalization techniques and experience with data warehousing concepts, are highly valued. Effective communication, attention to detail, and problem-solving abilities set outstanding data modelers apart, allowing them to convey complex concepts to both technical and non-technical stakeholders. These skills are vital for building accurate, scalable data models that serve as the foundation for reliable data-driven decision-making within organizations.

How much do data modelers make?

Data modelers typically earn a median annual salary between $80,000 and $120,000, depending on experience, location, and industry. Senior data modelers with advanced skills in database design and data warehousing can earn higher salaries, often exceeding $130,000. Certifications in data management and proficiency with tools like SQL and ER modeling can also influence compensation.

Is data modeling a good career?

Data modeling is a valuable career in data management and analytics, involving designing and organizing data structures for databases and systems. It requires skills in database tools, understanding of business requirements, and often benefits from certifications like CBIP or data modeling tools such as ERwin or PowerDesigner. The role offers opportunities in various industries with a focus on data quality and efficiency.

Is data modeling hard to learn?

Data modeling can be challenging for beginners due to the need to understand database structures, relationships, and normalization concepts. However, with consistent study, practice, and familiarity with tools like ER diagrams and SQL, many learners can develop proficiency over time.
Infographic showing various Data Modeling 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, with an average salary of $112,760 per year, or $54.2 per hour.

Staff Data Engineer

Flywheel Bakken LLC

Oklahoma City, OK โ€ข On-site

$140 - $200/hr

Other

Posted 5 days ago


Job description

Staff Data Engineer# Staff Data EngineerOklahoma City Office - Oklahoma City, OK 73102## Description## Job SummaryAs a Staff Data Engineer, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis across our upstream operations. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions that support the business as it scales. As a Staff level engineer, you will mentor and inspire high-performing teams. Additionally, this position collaborates with crossโ€functional teams to integrate databases with applications, support ETL workflows, and enable scalable cloud-based solutions. The role also includes performance monitoring, capacity planning, disaster recovery preparation, and maintaining comprehensive documentation to support reliable and resilient data operations.In this role within a fast-growing oil and gas company with significant momentum, you will leverage advanced technologies and techniques to design and develop robust data solutions for the business. You will transform raw field, production, and operational data into actionable insights, enabling informed decision-making and driving business growth. By using a broad range of tools, methodologies, and techniques, you will generate new ideas and solve problems, contributing to the overall strategy and objectives of our data team as we lead the company through this next stage of growth.## ## Key Responsibilities1. Design, build, and maintain scalable data pipelines that ingest, transform, and deliver upstream production, field, and operational data to downstream business teams.2. Develop and optimize ETL/ELT workflows to support reporting, analytics, and operational decision-making across the business.3. Architect and implement data integration solutions that connect source systems (SCADA, ERP, production databases, third-party data feeds) with the company's data warehouse/lake environment.4. Demonstrate expertise in data architecture, with a track record of designing scalable, well-structured data models and systems that avoid technical debt and support long-term maintainability.5. Collaborate with cross-functional teams, including analytics, engineering, and operations, to translate business requirements into reliable data solutions.6. Establish and maintain data quality, validation, and governance standards across pipelines and datasets.7. Monitor pipeline and system performance, proactively identifying and resolving bottlenecks, failures, and inefficiencies.8. Lead capacity planning efforts to ensure infrastructure scales alongside business growth.9. Develop and maintain disaster recovery procedures to support resilient, highly available data operations.10. Maintain comprehensive technical documentation for data architecture, pipelines, and operational processes.11. Evaluate and recommend tools, platforms, and best practices to continuously improve the data engineering function.12. Mentor junior and mid-level engineers, providing technical guidance and supporting their professional growth.13. Partner with leadership to align data engineering priorities with the company's broader strategic and growth objectives.## Qualifications## Required Qualifications1. Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience2. 7+ years of experience in data engineering, with demonstrated experience designing and scaling production data pipelines.3. Hands-on experience with one of the major cloud data warehouse/data lake platforms (e.g., Databricks, Snowflake, or Microsoft Fabric); platform-agnostic mindset preferred, with the ability to ramp quickly on whichever platform the business standardizes on.4. Strong proficiency in SQL, Python, and API.5. Experience building and orchestrating ETL/ELT workflows using tools such as Azure Data Factory, dbt, Airflow, or equivalent6. Solid understanding of data modeling, data warehousing concepts, and distributed data processing7. Experience working with cloud platforms (Azure, AWS, or GCP) and cloud-native data services8. Demonstrated experience with performance monitoring, capacity planning, and disaster recovery practices for data systems9. Strong collaboration skills, with experience partnering across engineering, analytics, and business teams to deliver scalable solutions.10. Ability to manage multiple priorities in a fast-paced environment.11. Willingness to perform occasional after-hours critical support and maintenance, depending on business needs.## Preferred Qualifications1. Oil and gas industry experience, particularly with upstream data (production volumes, well data, SCADA, or similar).2. Familiarity with oil and gas industry software and applications.3. Experience integrating or extracting data from oil and gas-specific systems, including SCADA, production accounting, land management, or reserves/engineering applications.4. Experience mentoring or providing technical guidance to junior engineers.5. Experience with cloud databases (e.g., AWS RDS, Azure SQL Database, Google Cloud SQL) and big data tools (e.g., Hadoop, Spark).6. Knowledge of cybersecurity and data protection best practices (Microsoft Entra and other IAM tools)7. Understanding of data warehousing, BI tools (e.g., Power BI), and automation scripting (e.g., SQL, Python, Bash, SSRS, KQL, Graph API). #J-18808-Ljbffr