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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer II - **Company:** Love’s Travel Stops & Country Stores, Inc. - **Location:** Oklahoma City, OK, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Application Programming Interfaces (APIs), Artificial Intelligence, Build Automation, Information Engineering, Data Governance, Data Hub, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Programming Tools, R (Programming Language), Python (Programming Language), Enterprise Messaging Systems, Meta-Data Management, Microsoft SQL Server, Release Management, Power BI, DataOps, SAP HANA, SQL Databases, Tableau (Software), Transaction Data, Azure Service Bus, Freeform SQL, Cloud Platform System, GitHub Copilot, Claude Code, Snowflake, Change Data Capture, Backend, Git, Data Lakes, Information Technology, Enterprise Integration, Apache Kafka, Apache Nifi, Data Management, Database Replication, Api Design, Software Version Control, Data Pipelines - **Published:** October 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c48144a229a66173 ## About the Role 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. ## Description 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.