Data Engineer

• Design, build, and maintain ETL/ELT pipelines that process high‑volume operational and logistics data
• Develop transformation logic and automation using Python, SQL, and Azure-native tooling
• Implement and orchestrate workflows in Azure Data Factory, Synapse, and Databricks
• Optimize data lake and warehouse performance, including tuning queries, pipelines, and storage layers
• Monitor pipeline health and proactively troubleshoot failures, bottlenecks, and data quality issues
• Contribute to data modeling efforts to support analytics, reporting, and downstream applications
• Collaborate with BI, product, supply chain, and application teams to align pipelines with business needs
• Maintain strong documentation around workflows, standards, and operational procedures
• Support governance initiatives related to data quality, lineage, cataloging, and access policies
• Follow best practices for security, compliance, and cloud resource management

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

experience with logistics, transportation, or supply chain data flows

• medical, vision, dental, and life and disability insurance
• eligible to enroll in our company 401(k) plan