Data Engineer IFS Logistics

Data Connect is the trusted unified logistics data layer that everything else at 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.

Were hiring a Data Engineer to help build and run that platform. This is a hands-on individual-contributor role youll 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. Its a strong fit if youve 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 youll 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 teams 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

Qualifications :

Core experience

• 2 years production experience as a Data Engineer or in a closely adjacent backend/data role
• Strong in SQL comfortable with dimensional data modelling (Kimball star schema normal forms)
• Strong in Python including unit testing functional testing and data quality checks
• Experience with a cloud data platform (BigQuery Snowflake or similar) and an ELT tool such as dbt
• Experience with BI tools (Superset Looker Power BI)
• Experience building APIs and comfortable reading Django or FastAPI source code

Data engineering fundamentals

• Understands schema evolution partitioning and incremental loads
• Familiar with streaming/event tooling (Pub/Sub Kafka Datastream or similar) you dont need to have designed one from scratch
• Uses version control properly (GitHub/GitLab) and writes tests for pipeline logic
• Comfortable using LLMs and AI coding tools for rapid debugging and prototyping

Ways of working

• Comfortable asking for direction on architecture calls but takes full ownership of building and running whats assigned
• Clear proactive communicator flags risk early rather than after an SLA is missed
• Curious about the logistics domain rather than treating data as generic rows and columns

Nice to have

• Experience with OCR/document-parsing tools (Tesseract Textract) or supply chain documents (POs invoices airway bills)
• Exposure to infrastructure-as-code (Terraform) or Kubernetes
• Prior logistics supply chain or B2B SaaS data experience
• Exposure to ML NLP generative AI forecasting or analytics pipelines

Tech stack

• Warehouse/lakehouse: BigQuery.
• Transformation: dbt.
• Visualisation: Cube Cloud Superset.
• Streaming/integration: Pub/Sub Datastream.
• Languages: Python SQL.
• Infra: GCP Kubernetes Terraform CI/CD K8s.

Additional Information :

We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles while also valuing inclusive workplace experiences. By fostering a sense of community we drive innovation strengthen connections and nurture belonging. Our commitment ensures you can work in a way that suits you best while also engaging with colleagues to share ideas and build meaningful relationships.

Remote Work :

No

Employment Type :

Full-time