Data Engineer (Cloud Lakehouse / ETL)
Location: Remote or Memphis, TN (Hybrid)
Overview
We are seeking a hands-on Data Engineer to support enterprise data transformation, data movement, and operational data processing initiatives within a modern cloud-based data platform environment.
This role focuses on building, enhancing, and supporting large-scale ETL and data integration processes while ensuring enterprise data remains accurate, highly available, and optimized for performance. The ideal candidate will have strong experience with SQL, ETL/data pipelines, cloud technologies, and production troubleshooting within enterprise environments.
This position supports critical overnight data processing operations and requires flexibility to work an afternoon/evening schedule with occasional extended support hours as needed.
Key Responsibilities
Support and enhance enterprise ETL and nightly data load processes Develop, maintain, and optimize scalable data pipelines and integration workflows Ensure enterprise data quality, reliability, availability, and performance Contribute to the optimization and operational support of a cloud-based data platform environment Troubleshoot and resolve production data processing and pipeline issues Work across internal and external systems to extract, transform, and load enterprise data Collaborate with business analysts, technical teams, and stakeholders to support data initiatives and enhancements Participate in Agile/Scrum ceremonies and collaborate within cross-functional engineering teams Contribute to automated testing and continuous improvement initiatives Analyze existing systems and recommend improvements related to scalability, maintainability, and performance Design, develop, test, debug, document, and support data integration and application solutions
Required Qualifications
Bachelors degree in Computer Science, Information Systems, Engineering, Mathematics, or related technical field 3+ years of experience in Data Engineering, ETL Development, or related software engineering roles Strong SQL development and query optimization experience Hands-on experience with ETL/data integration solutions Experience supporting enterprise-scale data processing environments Experience troubleshooting production data pipeline and load issues Experience working in Agile/Scrum or similar collaborative development environments Strong analytical, debugging, and problem-solving skills Ability to work independently in a fast-paced operational environment
Preferred Qualifications
Experience with cloud-based data platforms or Lakehouse architectures Experience with technologies such as AWS, Redshift, S3, Lambda, DBT, or related cloud data tools Enterprise data warehouse experience Experience with SSIS or SSDT Experience with data pipeline optimization and performance tuning Exposure to CI/CD practices and automated testing Experience supporting operational or overnight data processing environments
How to Apply
Qualified candidates are encouraged to submit an updated resume for confidential consideration. We welcome candidates with strong hands-on Data Engineering, ETL, SQL, and cloud data platform experience who are interested in supporting large-scale enterprise data operations.
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