Data Engineer I

Benefits and culture

Murphy USA offers an on-site Data Engineer I role in El Dorado, Arkansas. You will contribute to building and supporting data products in a cloud-based data lake, enabling enterprise analytics and data driven decision making. The position emphasizes collaboration across business units and peer technology teams, clean code practices, and proactive maintenance to help reduce technical debt.

• On-site opportunity in El Dorado, AR
• Work on a cloud-based data lake and enterprise analytics programs
• Collaborate with business units and technology peers to drive analytics initiatives
• Focus on data quality, security, reusability, and maintainability of data pipelines
• Hands-on work with a modern stack including Python, SQL, PySpark and infrastructure tools

Responsibilities

• Develop and support data products on a modern cloud-based data lake, applying expertise across multiple technologies and data domains to build a robust, scalable platform
• Provide data services for enterprise-grade analytics environments by implementing automated pipelines at scale and enabling efficient data transformations for priority use cases
• Contribute hands-on in code development and partner with business units and peer technology groups to support analytics execution
• Collaborate across the organization to architect, implement, deploy, and maintain data-driven systems
• Build, maintain, and simplify enterprise data pipelines with an emphasis on security, reusability, and data quality
• Debug and resolve application issues, perform root cause analysis, and assist with preventive maintenance
• Support technical debt reduction and follow clean code principles
• Development experience in one or more languages such as Python, SQL, or PySpark
• Experience with Infrastructure as Code tools including Databricks Asset Bundled and Terraform
• Engage with the data governance council to define and review standards, guidelines, and data models to promote data quality
• Leverage DevOps practices to automate deployment and validation/testing of data pipelines
• Write and execute comprehensive testing plans, protocols, and documentation for data system components
• Identify defects and develop solutions for issues with code and integration into the data architecture
• Plan and collaborate effectively with technical and non-technical teams on business initiatives

Technologies frequently used

• Python
• SQL
• PySpark
• Databricks Asset Bundled
• Terraform