Data Engineer

• ELT frameworks , Fivetran , Python , Snowflake

Our client is building the next generation of cross-border logistics infrastructure for modern trade between the U.S. and Mexico. They combine technology, data, and operational excellence to streamline freight forwarding, customs brokerage, and end-to-end supply chain visibility.

They operate in a fast-paced, execution-driven environment where data is treated as a strategic asset powering operational efficiency, financial accuracy, and product innovation.

Our client is hiring a Data Engineer to design, build, and scale their core data infrastructure. This role is critical to ensuring reliable, well-modeled, and accessible data across the organization.

The selected candidate will work closely with Operations, Finance, Product, and Sales teams to enable decision-making through high-quality data pipelines, analytics-ready models, and automation systems. This position requires strong technical execution and the ability to operate effectively in a high-growth environment.

• End-to-end ELT pipelines using Fivetran, dbt, and Snowflake, ensuring high standards of reliability, performance, scalability, and observability.
• Data orchestration workflows using dbt Cloud and Prefect, including scheduling, monitoring, alerting, and continuous optimization of dependencies.
• Analytics-ready data models that support Operations, Finance, Product, and Sales, with emphasis on data integrity, documentation, governance, and performance tuning.
• AI agents and automation workflows tailored to logistics use cases, increasing operational efficiency, reducing manual intervention, and enabling intelligent decision automation.
• Continuous improvement of data quality frameworks, testing strategies, and transformation best practices across the modern data stack.

• 3+ years of hands-on data engineering experience in production-grade environments.
• Strong expertise in dbt and Snowflake, including advanced data modeling techniques, cost optimization, and query performance tuning.
• Solid Python proficiency for complex pipeline development, API integrations, and workflow automation.
• Experience using AI-assisted development tools to accelerate engineering workflows and improve code quality.
• Deep understanding of ELT architecture, data warehousing concepts, and data lifecycle management.
• Comfort collaborating cross-functionally in a fast-moving, high-accountability environment with clear ownership expectations.