Data Engineer II

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, and supports scalable data solutions that advance Love’s enterprise data and analytics capabilities. This role develops and optimizes data pipelines, data models, and integration frameworks that transform data into reliable, accessible, and actionable information.

The Data Engineer II partners with Technology teams, business stakeholders, data scientists, data analysts, vendors, and other data consumers to operationalize data and analytics solutions. The position also provides technical guidance on data architecture, promotes reusable design standards, and uses automation and AI-powered development tools to improve delivery speed, quality, and consistency.

• 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 Data Ops and Dev Ops 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 Git Hub Copilot, Claude Code, or similar technologies, to accelerate delivery, reduce defects, improve documentation, strengthen automation, and increase consistency throughout the Data Ops 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.

• 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…