Data Engineer II

This role designs, builds, maintains, and supports data solutions to improve Love’s enterprise data and analytics capabilities, with a focus on reliable delivery of information through pipelines, models, and integrations.

Role Responsibilities

• Design, build, maintain, and optimize data pipelines for 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 meet master, reference, and transactional data requirements.
• Conduct data assessment, mapping, migration, validation, enrichment, and loading activities.
• Create 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 centered 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 impact solution design, development, testing, implementation, and ongoing support.
• Collaborate with business and Technology partners to convert 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 across 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.

Required Qualifications

• Bachelor’s degree in Computer Science, Management Information Systems, Information Technology, Business, or a related field (typically required).
• Two or more years of related experience in data engineering, data integration, data warehousing, or a related technical discipline.
• Experience building and supporting data pipelines, integration solutions, large or varied datasets, cloud-based data platforms, and modern data-management environments.
• Working knowledge of data engineering, data integration, data warehousing, and data-management principles.
• General proficiency with cloud data warehouse platforms, preferably Snowflake, and experience 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.
• 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 to both technical and nontechnical audiences.
• Strong written and verbal communication, analytical and problem-solving skills, troubleshooting ability, accountability, initiative, and attention to detail.
• Commitment to ethical conduct, regulatory compliance, customer service, data stewardship, and business integrity.

Preferred Qualifications

• Experience with dbt.
• Experience with Python or R, Microsoft SQL Server, SAP HANA, Tableau, Power BI, and AI-powered development tools.

Technologies

• ETL, ELT, SQL, Snowflake
• Git, Fivetran, HVR
• Azure Service Bus, Apache NiFi, Apache Kafka, APIs
• dbt, Python, R, Microsoft SQL Server, SAP HANA
• Tableau, Power BI
• GitHub Copilot, Claude Code
• DataOps, DevOps

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

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.

Location and Work Setting

Oklahoma City, OK (onsite)

About the Culture

Fueling customers’ journeys since 1964, Love’s is a family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are central to the business, supported by products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and maintaining an inclusive workplace are hallmarks of the award-winning culture.