Data Engineer - IFS Logistics

Data Connect is the trusted, unified logistics data layer that everything else at IFS.ai Logistics depends on — carrier, shipment, invoice and ERP data from dozens of fragmented sources, turned into one model that Transport Planning & Optimization and Shipper TMS both build on. Work here has outsized leverage: fix a pipeline in Data Connect and the improvement is felt across the whole platform.

We're hiring a Data Engineer to help build and run that platform. This is a hands-on, individual-contributor role — you'll own delivery of pipelines and platform features end-to-end within your area, working under the direction of the Lead Data Engineer rather than setting platform architecture yourself. It's a strong fit if you've got a couple of years of production data engineering experience and want to grow into more ownership over time, with senior engineers around you to learn from rather than being the most senior person in the room from day one.

What you'll work on

• Pipelines and ingestion — build and maintain ETL/ELT pipelines that turn carrier, shipment, invoice and ERP data into the canonical Data Connect model; work on document data extraction (OCR/parsing for airway bills, POs, commercial invoices); extend carrier and ERP integrations and help onboard new data sources; implement data contract checks, validation and reconciliation so downstream teams can trust what they consume
• Platform and data quality — keep the pipelines you own within their performance and quality SLAs; when something breaks in your area, you can typically run it down in a couple of hours, not days; contribute to dimensional models (star/snowflake schemas) to a design set by a senior/lead; follow the team's standards for testing, version control and observability
• Collaboration — work closely with the Lead Data Engineer, Data Scientists and Software Engineers on pipeline design; document what you build so analysts across Product, Data Science and Customer Success can self-serve rather than asking you
What success looks like

• Owns and reliably operates a defined slice of the pipeline estate, within its SLAs
• Ships pipeline and data features on the roadmap without needing close supervision
• Debugging and data-quality issues in your area get resolved fast, and documented so others can self-serve next time
• Trusted by the Lead Data Engineer to take on larger, less-defined problems over time

Department: Research and Development
Function: Information Technology
Experience Level: Mid-Senior Level