<p><strong>Senior Data Engineer</strong></p><p><strong>Contract</strong>: Through 12/31/26 (Extensions Likely)</p><p><strong>Remote working EST Hours</strong></p><p><br></p><p><u>NOTE: Though this role is remote, candidates will need to complete an ONSITE interview in Philadelphia, PA for a 2nd [final] round (if requested).</u></p><p><br></p><p><br></p><p>We are seeking a Senior Data Engineer to support a high-impact Salesforce initiative focused on large-scale data migration and pipeline development into Databricks for a major advertising platform. This long-term remote contract role centers on building and optimizing ETL pipelines using Python, Spark, and PySpark within an AWS environment, enabling seamless data integration between Salesforce and modern data platforms. The position collaborates closely with cross-functional engineering teams to deliver scalable, reliable data solutions, improve deployment processes through CI/CD and infrastructure-as-code practices, and ensure the overall quality, performance, and resilience of critical data systems.</p><p><br></p><p><strong>Responsibilities:</strong></p><ul><li>Develop <strong>ETL pipelines</strong> to migrate and integrate data into <strong>Databricks</strong></li><li>Support <strong>Salesforce to Databricks data migration and integration</strong></li><li>Design, build, test, and maintain <strong>data pipelines on AWS + Databricks</strong></li><li>Translate business requirements into <strong>scalable data engineering solutions</strong></li><li>Contribute to <strong>data warehousing components</strong> for Salesforce Phase 2</li><li>Utilize <strong>Terraform</strong> for infrastructure provisioning and management</li><li>Implement and maintain <strong>CI/CD pipelines</strong> (Concourse or GitHub Actions)</li><li>Perform <strong>testing, QA, and documentation</strong> for all data engineering work</li><li>Provide <strong>post-deployment support and troubleshooting</strong></li><li>Identify and mitigate risks, including <strong>single points of failure (SPOF)</strong></li><li>Collaborate within Agile teams and participate in <strong>weekly Scrum ceremonies</strong></li><li>Work closely with senior engineers and contribute to <strong>best practices and knowledge sharing</strong></li></ul>

<p><strong>Requirements: </strong></p><ul><li><strong>7–9 years</strong> of experience in <strong>data engineering / data integration projects</strong></li><li>Strong hands-on experience with:</li><li><b>Spark / PySpark (required)</b></li><li><strong>Python for ETL development (required)</strong></li><li><strong>Databricks (required)</strong></li><li>Experience building <strong>data pipelines in AWS environments</strong></li><li>Knowledge of <strong>data migration and integration frameworks</strong></li><li>Experience with <strong>Terraform (infrastructure as code)</strong></li><li>Familiarity with <strong>CI/CD tools</strong> (Concourse, GitHub Actions)</li><li>Experience working in <strong>Agile/Scrum environments</strong></li><li>Strong troubleshooting and problem-solving skills</li></ul><p><br></p><p><strong>Preferred Qualifications:</strong></p><ul><li>Java development experience</li><li>Salesforce data/model knowledge</li><li>Mulesoft experience</li></ul>

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