Big Data Engineer Visa Sponsorship Jobs in Oklahoma
Big data engineer visa sponsorship jobs in Oklahoma are concentrated in Oklahoma City and Tulsa, where energy giants like Devon Energy and ONEOK, aerospace firms, and growing fintech companies build data infrastructure. Oklahoma's energy sector generates massive datasets that drive consistent demand for engineers skilled in distributed systems, cloud pipelines, and large-scale analytics platforms.
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Get Access To All JobsBenefits:
* Fuel Your Growth with Love's - company funded tuition assistance
* Paid Time Off
* 401(k) – 100% Match up to 5%
* Medical/Dental/Vision Insurance after 30 days
* Competitive Pay
* Career Development
Welcome to Love's:
The Data Engineer II designs, builds, maintains, and supports data solutions that strengthen Love’s enterprise data and analytics capabilities. The role develops and optimizes data pipelines, data models, and integration processes that transform data into reliable, accessible, and actionable information. Working under general supervision, this position handles assignments of moderate scope, exercises judgment within established procedures and practices, and builds productive working relationships with Technology teams, business stakeholders, data analysts, data scientists, vendors, and other data consumers. The role applies working knowledge of modern data engineering practices and consults more experienced team members on complex technical issues as needed.
MAJOR RESPONSIBILITIES:
- Design, build, maintain, and optimize data pipelines supporting data acquisition, ingestion, transformation, staging, modeling, and delivery.
- Develop data integration solutions using ETL/ELT, data replication, change data capture, messaging technologies, APIs, and other data movement methods.
- Evaluate and qualify source data to support master, reference, and transactional data requirements.
- Perform data assessment, mapping, migration, validation, enrichment, and loading activities.
- Develop reusable data models and solution components using established data engineering and modeling practices.
- Build and support data solutions across data warehouse, data lake, data hub, and related data-management environments.
- Integrate large, complex, and heterogeneous datasets from internal and external sources.
- Develop solutions that are reliable, secure, scalable, maintainable, and focused on automation and operational efficiency.
- Develop and maintain complex SQL queries, procedures, transformations, and data-validation processes.
- Apply DataOps and DevOps practices, including version control, automated builds, testing, deployment, monitoring, and release management.
- Troubleshoot data quality, integration, performance, and production-support issues, escalating highly complex matters when appropriate.
- Participate in front-end and back-end development activities when needed to deliver integrated, end-to-end data solutions.
- Assess how technical decisions affect solution design, development, testing, implementation, and ongoing support.
- Collaborate with business and Technology partners to translate data requirements into effective technical solutions.
- Use AI-powered development tools, such as GitHub Copilot, Claude Code, or similar technologies, to improve delivery speed, quality, documentation, automation, and consistency throughout the DataOps lifecycle.
- Research and recommend tools, technologies, and practices that improve data engineering capabilities and team productivity.
- Share knowledge and provide technical support to team members within the scope of assigned work.
- Perform other job-related duties as assigned.
EDUCATION AND EXPERIENCE:
Education:
Bachelor’s degree in Computer Science, Management Information Systems, Information Technology, Business, or a related field typically required.
Experience:
Two or more years of related experience in data engineering, data integration, data warehousing, or a related technical discipline required.
Experience building and supporting data pipelines, integration solutions, large or varied datasets, cloud-based data platforms, and modern data-management environments required.
SKILLS AND PHYSICAL DEMANDS:
Skills:
- Working knowledge of data engineering, data integration, data warehousing, and data-management principles.
- General proficiency with cloud data warehouse platforms, preferably Snowflake, and with developing and optimizing complex SQL.
- Experience with ETL/ELT tools and methodologies, data modeling, reusable solution components, and Git or similar version-control tools.
- Understanding of automated build, testing, deployment, monitoring, and release-management practices.
- Experience with data replication and change data capture tools, such as Fivetran or HVR.
- Experience with messaging and data movement technologies, such as Azure Service Bus, Apache NiFi, or Apache Kafka.
- Experience with APIs and API-based data acquisition and integration.
- Knowledge of data governance, metadata management, data quality, and master-data concepts.
- Understanding of solution architecture and its impact on design, development, testing, deployment, and support.
- Experience with dbt strongly preferred. Experience with Python or R, Microsoft SQL Server, SAP HANA, Tableau, Power BI, and AI-powered development tools preferred.
- Ability to analyze and resolve issues of moderate scope using established procedures, sound judgment, and appropriate escalation.
- Ability to manage changing priorities, collaborate effectively, and communicate technical information clearly to technical and nontechnical audiences.
- Strong written and verbal communication, analytical, problem-solving, troubleshooting, accountability, initiative, and attention to detail.
- Commitment to ethical conduct, regulatory compliance, customer service, data stewardship, and business integrity.
Typical Physical Demands:
Requires prolonged sitting, some bending and stooping.
Frequent computer and screen use, with manual dexterity sufficient to operate a computer keyboard and calculator.
Occasional lifting up to 25 pounds.
Requires normal range of hearing and vision.
Additional hours may be necessary.
Our Culture:
Fueling customers' journeys since 1964, innovation leads the way for this family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are the core business along with products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and an inclusive workplace are hallmarks of the award-winning culture.
Love's is an Equal Opportunity Employer. Veterans encouraged to apply.
Benefits:
* Fuel Your Growth with Love's - company funded tuition assistance
* Paid Time Off
* 401(k) – 100% Match up to 5%
* Medical/Dental/Vision Insurance after 30 days
* Competitive Pay
* Career Development
Welcome to Love's:
The Data Engineer II designs, builds, maintains, and supports data solutions that strengthen Love’s enterprise data and analytics capabilities. The role develops and optimizes data pipelines, data models, and integration processes that transform data into reliable, accessible, and actionable information. Working under general supervision, this position handles assignments of moderate scope, exercises judgment within established procedures and practices, and builds productive working relationships with Technology teams, business stakeholders, data analysts, data scientists, vendors, and other data consumers. The role applies working knowledge of modern data engineering practices and consults more experienced team members on complex technical issues as needed.
MAJOR RESPONSIBILITIES:
- Design, build, maintain, and optimize data pipelines supporting data acquisition, ingestion, transformation, staging, modeling, and delivery.
- Develop data integration solutions using ETL/ELT, data replication, change data capture, messaging technologies, APIs, and other data movement methods.
- Evaluate and qualify source data to support master, reference, and transactional data requirements.
- Perform data assessment, mapping, migration, validation, enrichment, and loading activities.
- Develop reusable data models and solution components using established data engineering and modeling practices.
- Build and support data solutions across data warehouse, data lake, data hub, and related data-management environments.
- Integrate large, complex, and heterogeneous datasets from internal and external sources.
- Develop solutions that are reliable, secure, scalable, maintainable, and focused on automation and operational efficiency.
- Develop and maintain complex SQL queries, procedures, transformations, and data-validation processes.
- Apply DataOps and DevOps practices, including version control, automated builds, testing, deployment, monitoring, and release management.
- Troubleshoot data quality, integration, performance, and production-support issues, escalating highly complex matters when appropriate.
- Participate in front-end and back-end development activities when needed to deliver integrated, end-to-end data solutions.
- Assess how technical decisions affect solution design, development, testing, implementation, and ongoing support.
- Collaborate with business and Technology partners to translate data requirements into effective technical solutions.
- Use AI-powered development tools, such as GitHub Copilot, Claude Code, or similar technologies, to improve delivery speed, quality, documentation, automation, and consistency throughout the DataOps lifecycle.
- Research and recommend tools, technologies, and practices that improve data engineering capabilities and team productivity.
- Share knowledge and provide technical support to team members within the scope of assigned work.
- Perform other job-related duties as assigned.
EDUCATION AND EXPERIENCE:
Education:
Bachelor’s degree in Computer Science, Management Information Systems, Information Technology, Business, or a related field typically required.
Experience:
Two or more years of related experience in data engineering, data integration, data warehousing, or a related technical discipline required.
Experience building and supporting data pipelines, integration solutions, large or varied datasets, cloud-based data platforms, and modern data-management environments required.
SKILLS AND PHYSICAL DEMANDS:
Skills:
- Working knowledge of data engineering, data integration, data warehousing, and data-management principles.
- General proficiency with cloud data warehouse platforms, preferably Snowflake, and with developing and optimizing complex SQL.
- Experience with ETL/ELT tools and methodologies, data modeling, reusable solution components, and Git or similar version-control tools.
- Understanding of automated build, testing, deployment, monitoring, and release-management practices.
- Experience with data replication and change data capture tools, such as Fivetran or HVR.
- Experience with messaging and data movement technologies, such as Azure Service Bus, Apache NiFi, or Apache Kafka.
- Experience with APIs and API-based data acquisition and integration.
- Knowledge of data governance, metadata management, data quality, and master-data concepts.
- Understanding of solution architecture and its impact on design, development, testing, deployment, and support.
- Experience with dbt strongly preferred. Experience with Python or R, Microsoft SQL Server, SAP HANA, Tableau, Power BI, and AI-powered development tools preferred.
- Ability to analyze and resolve issues of moderate scope using established procedures, sound judgment, and appropriate escalation.
- Ability to manage changing priorities, collaborate effectively, and communicate technical information clearly to technical and nontechnical audiences.
- Strong written and verbal communication, analytical, problem-solving, troubleshooting, accountability, initiative, and attention to detail.
- Commitment to ethical conduct, regulatory compliance, customer service, data stewardship, and business integrity.
Typical Physical Demands:
Requires prolonged sitting, some bending and stooping.
Frequent computer and screen use, with manual dexterity sufficient to operate a computer keyboard and calculator.
Occasional lifting up to 25 pounds.
Requires normal range of hearing and vision.
Additional hours may be necessary.
Our Culture:
Fueling customers' journeys since 1964, innovation leads the way for this family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are the core business along with products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and an inclusive workplace are hallmarks of the award-winning culture.
Love's is an Equal Opportunity Employer. Veterans encouraged to apply.
Big Data Engineer Job Roles in Oklahoma
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Search Big Data Engineer Jobs in OklahomaBig Data Engineer Jobs in Oklahoma: Frequently Asked Questions
Which companies in Oklahoma sponsor visas for big data engineers?
Energy companies are the most active sponsors in Oklahoma, with firms like Devon Energy, Continental Resources, and ONEOK building data engineering teams to process exploration and production datasets. Aerospace and defense contractors around Tulsa, along with regional banks and insurance companies in Oklahoma City, also sponsor big data engineers. University of Oklahoma and Oklahoma State University occasionally sponsor roles through research and IT divisions.
Which visa types realistically apply to big data engineer roles in Oklahoma?
Big data engineering is a specialty occupation requiring a bachelor's degree in computer science, information systems, or a related field, so the H-1B visa is the most common path. Canadian and Mexican nationals may qualify under the TN visa as engineers, provided they hold the required engineering or computer science degree. F-1 graduates can work via OPT or STEM OPT if their degree is STEM-designated. EB-2 and EB-3 green cards are available for longer-term sponsorship.
Which cities in Oklahoma have the most big data engineer sponsorship jobs?
Oklahoma City generates the highest volume of big data engineer openings, driven by energy sector headquarters and a growing financial technology sector. Tulsa is the second major hub, with aerospace, manufacturing, and energy midstream companies maintaining data engineering teams. Norman and Stillwater see smaller but steady demand linked to the University of Oklahoma and Oklahoma State University research computing environments.
How to find big data engineer visa sponsorship jobs in Oklahoma?
Migrate Mate lists big data engineer positions at Oklahoma employers with verified visa sponsorship history, searchable by city and role. Because energy companies dominate Oklahoma's tech hiring, filtering specifically for data engineering roles in sectors like oil and gas, aerospace, and financial services helps narrow to the most active sponsors. Migrate Mate surfaces employers based on documented sponsorship activity, so you're not applying blind.
Are there any Oklahoma-specific factors that affect big data engineer visa sponsorship?
Oklahoma's economy is heavily tied to energy, so big data engineers who bring experience with time-series data, sensor telemetry, or geospatial analytics have a stronger fit with the state's largest sponsors. The University of Oklahoma and Oklahoma State University produce engineering graduates who sometimes transition directly into sponsored roles at energy and aerospace employers. Oklahoma has a relatively lower cost of living than coastal tech hubs, which can affect prevailing wage levels filed on Labor Condition Applications.
What is the prevailing wage for sponsored big data engineer jobs in Oklahoma?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.