<p>Our transportation client is seeking a <strong>Data Engineer</strong> to support large‑scale logistics operations by building reliable, scalable, and cloud‑based data pipelines. This role is hands‑on, focused on delivering high‑quality data flows that improve shipment visibility, operational efficiency, and real‑time analytics across the supply chain.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, build, and maintain <strong>ETL/ELT pipelines</strong> that process high‑volume operational and logistics data</li><li>Develop transformation logic and automation using <strong>Python</strong>, <strong>SQL</strong>, and Azure-native tooling</li><li>Implement and orchestrate workflows in <strong>Azure Data Factory</strong>, <strong>Synapse</strong>, and <strong>Databricks</strong></li><li>Optimize data lake and warehouse performance, including tuning queries, pipelines, and storage layers</li><li>Monitor pipeline health and proactively troubleshoot failures, bottlenecks, and data quality issues</li><li>Contribute to data modeling efforts to support analytics, reporting, and downstream applications</li><li>Collaborate with BI, product, supply chain, and application teams to align pipelines with business needs</li><li>Maintain strong documentation around workflows, standards, and operational procedures</li><li>Support governance initiatives related to <strong>data quality</strong>, lineage, cataloging, and access policies</li><li>Follow best practices for security, compliance, and cloud resource management</li></ul><p><br></p><p><br></p>

<p><br></p><p><strong>Requirements</strong></p><ul><li><strong>3+ years</strong> of experience in data engineering or data pipeline development</li><li>Strong proficiency in <strong>SQL</strong> (complex joins, window functions, performance tuning)</li><li>Hands-on experience using <strong>Python</strong> for data transformations, automation, and ETL scripting</li><li>Experience with cloud data ecosystems, ideally <strong>Azure</strong> (Data Factory, Synapse, Databricks)</li><li>Understanding of <strong>data lakehouse</strong> design, warehousing concepts, and distributed processing</li><li>Familiarity with <strong>CI/CD pipelines</strong>, Git‑based version control, and modern DevOps practices</li><li>Experience working with <strong>large datasets</strong>, streaming or batch processing environments</li><li>Ability to analyze pipeline issues, diagnose root causes, and improve system reliability</li><li>Strong communication skills and comfort partnering with cross-functional teams</li><li>Bonus: experience with logistics, transportation, or supply chain data flows</li></ul><p><br></p>

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