ICAT Logistics is seeking a Data Engineer responsible for designing, building, and maintaining data pipelines and storage systems that support analytics and AI-driven solutions in logistics. The role involves ensuring data accuracy and accessibility from various systems while collaborating with cross-functional teams to optimize data models and pipelines.
Responsibilities:
- Design, build, and maintain dimensional and relational data models optimized for logistics workflows (shipments, quotes, invoices, routings, tracking events, carrier performance, etc.)
- Define data standards, naming conventions, and schema documentation to ensure consistency across the enterprise
- Align data warehouse structures with operations, finance, sales, and compliance reporting needs
- Work with outsourced development teams
- Develop scalable ETL/ELT pipelines to ingest data from:
- Transportation Management Systems (e.g., CargoWise, Magaya, MercuryGate, Descartes)
- Warehouse systems, yard systems, and barcode/RFID sources
- Carrier EDI/API feeds (air, ocean, LTL, TL, parcel)
- Customer integrations (via API, FTP, SFTP, VAN, SCAC matching, etc.)
- Implement automated workflows to ensure near-real-time visibility and reliable data refresh cycles
- Manage cloud data lake storage layers (raw, refined, curated zones)
- Design and optimize data warehouse schemas for analytics and BI consumption
- Implement partitioning, indexing, compression, and performance tuning strategies
- Develop automated data validation, error handling, audit, and reconciliation processes
- Ensure data integrity and traceability across ingestion, transformation, and publishing layers
- Work with compliance teams to align data handling with ITAR, CMMC, CTPAT, ITAR, SOC2, GDPR, and customer contractual requirements
- Partner with data analysts, BI developers, AI/ML engineers, and product teams to support dashboards, operational insights, and predictive analytics use cases
- Work with business teams (operations, finance, sales, customer service) to translate business rules into data logic
- Provide technical guidance on data availability, meaning, lineage, and usage best practices
- Other duties as assigned
Requirements:
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field
- 3+ years of direct experience building data pipelines in production environments within transportation, logistics, or supply chain industries
- Strong experience with: SQL, Python, and ETL/ELT frameworks
- Cloud data platforms (AWS, Azure, or GCP)
- Data warehouse technologies (Snowflake, Redshift, BigQuery, Synapse, or PostgreSQL)
- Data lake architecture patterns (object storage, Delta/Iceberg/Hudi formats, metadata management)
- Familiarity with logistics or supply chain systems and data structures
- TMS/WMS system databases (CargoWise, Magaya, WorldTrak, Descartes, MercuryGate, SAP TM, Manhattan, Blue Yonder, etc.)
- integrating EDI (X12, EDIFACT), API-driven vendors, or telematics data
- understanding of shipment lifecycle events, cost allocation, and carrier/payables workflows
- Exposure to MDM, data cataloging, or data governance frameworks
- Advanced skills with Microsoft Office products (with an emphasis on Word, PPT and Excel)