<p><strong>Data Engineer</strong></p><p><strong>Location: <u>100% REMOTE BUT MUST BE ABLE TO INTERVIEW ONSITE IN PHILADELPHIA, PA</u></strong></p><p><strong>Duration: Through 12/31/2026, extensions likely</strong></p><p><br></p><p>This is a senior-level Data Engineer opportunity supporting enterprise modernization and cloud migration initiatives within a large-scale Agile environment. The role focuses on designing and building modern data pipelines, enhancing legacy data platforms, and developing scalable data assets that support analytics and reporting. The ideal candidate is a hands-on Data Engineer with deep expertise in Databricks, PySpark, Python, and AWS services, and experience working within cloud-based data ecosystems undergoing transformation.</p><p><br></p><p><strong>Responsibilities:</strong></p><ul><li>Design, develop, and maintain scalable data engineering solutions using Databricks, Python, PySpark, and AWS.</li><li>Build, optimize, and support ETL processes and data pipelines for inventory, supply, and yield data initiatives.</li><li>Develop and maintain data assets that support enterprise analytics and Tableau reporting environments.</li><li>Support cloud migration and modernization efforts by transforming legacy data platforms into modern cloud-based solutions.</li><li>Enhance and maintain existing data engineering workflows while delivering new data pipeline capabilities.</li><li>Collaborate with cross-functional teams, including engineering, analytics, and business stakeholders, within an Agile Release Train (ART) environment.</li><li>Contribute to reducing technical debt through modernization of legacy data systems.</li><li>Implement scalable and reliable data processing solutions leveraging AWS services and cloud-native technologies.</li></ul><p><br></p>

<p><strong>Qualifications:</strong></p><ul><li>Strong background in Data Engineering with approximately 8 years of relevant experience preferred.</li><li>Hands-on experience with Databricks.</li><li>Strong programming experience with Python and PySpark.</li><li>Experience building, enhancing, and maintaining ETL processes and data pipelines.</li><li>Strong SQL development experience.</li><li>Experience working with AWS data processing services, including:</li><li>S3</li><li>EMR</li><li>Lambda</li><li>EventBridge</li><li>Experience supporting cloud migration and data platform modernization initiatives.</li><li>Experience working within modern cloud-based data ecosystems.</li><li>Ability to design and maintain scalable data engineering solutions in enterprise environments.</li></ul><p><strong>Preferred Qualifications:</strong></p><ul><li>Experience with Tableau or Looker environments.</li><li>Experience with Snowflake.</li><li>Experience with Kafka.</li></ul><p><br></p><p><br></p><p><br></p>

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