Data Engineer II

Love's Travel Stops is a family-owned business that has been fueling customers' journeys since 1964. The Data Engineer II is responsible for designing, building, and supporting scalable data solutions to enhance the company's data and analytics capabilities while collaborating with various stakeholders to operationalize data and analytics solutions.

Responsibilities:

• Design, build, maintain, and optimize data pipelines supporting data acquisition, ingestion, transformation, staging, modeling, and delivery
• Develop scalable 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
• Lead data assessment, mapping, migration, validation, enrichment, and loading activities
• Design reusable data models and solution architectures using established data engineering and modeling practices
• Provide architectural and technical input to ensure solutions align with enterprise data strategies, standards, and long-term platform objectives
• 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
• Design 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 complex data quality, integration, performance, and production support issues
• Participate in front-end and back-end development activities when needed to deliver integrated, end-to-end data solutions
• Assess how architecture 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 accelerate delivery, reduce defects, improve documentation, strengthen automation, and increase consistency throughout the DataOps lifecycle
• Research and recommend tools, technologies, and practices that improve data engineering capabilities and team productivity
• Provide technical guidance, knowledge sharing, and support to other team members
• Perform other job-related duties as assigned

Requirements:

• Three or more years of progressively responsible experience in data engineering, data integration, data warehousing, or a related technical discipline required
• Experience designing, building, and supporting enterprise-level data pipelines and integration solutions required
• Experience working with large, complex, and heterogeneous datasets required
• Experience supporting data warehouse, data lake, data hub, or similar data management architectures required
• Experience working in cloud-based data platforms and modern data engineering environments required
• Advanced knowledge of data engineering, data integration, and data warehousing principles
• Strong experience with cloud data warehouse platforms, preferably Snowflake
• Strong experience developing and optimizing complex SQL
• Strong experience with ETL and ELT tools and methodologies
• Strong experience with data modeling and reusable solution architecture practices
• Strong experience with Git or similar version-control tools
• Strong understanding of automated build, testing, deployment, 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
• High school diploma or equivalent required
• Experience with dbt strongly preferred
• Experience with Python or R preferred
• Experience with Microsoft SQL Server preferred
• Experience with SAP HANA preferred
• Experience with Tableau or Power BI preferred
• Experience using AI-powered development and productivity tools preferred