Data Engineer (Logistics)

Location: Hybrid in Nunspeet, Gelderland, Netherlands

Company

hirify.global is a global enterprise software company with 7,000+ employees and billion-dollar revenue, delivering AI-driven solutions for customers worldwide.

What you will do

• Build and maintain ETL/ELT pipelines that transform carrier, shipment, invoice, and ERP data into the canonical Data Connect model.
• Develop document data extraction using OCR and parsing, extend carrier and ERP integrations, and onboard new data sources.
• Implement data contracts, validation, reconciliation, testing, version control, observability, and data-quality checks.
• Contribute to dimensional models, including Kimball star schemas and snowflake schemas, following designs set by senior engineers.
• Own and operate an assigned part of the pipeline estate within performance and quality SLAs, resolving incidents and shipping roadmap features.
• Collaborate with the Lead Data Engineer, Data Scientists, and Software Engineers while documenting solutions for self-service analytics.

Requirements

• Approximately 2 years of production experience as a Data Engineer or in a closely adjacent backend/data role.
• Strong SQL skills and familiarity with dimensional data modelling, including Kimball star schemas and normal forms.
• Strong Python skills, including unit testing, functional testing, and data-quality checks.
• Experience with a cloud data platform such as BigQuery or Snowflake and an ELT tool such as dbt.
• Experience with BI tools such as Superset, Looker, or Power BI.
• Experience building APIs and comfort reading Django or FastAPI source code.
• Understanding of schema evolution, partitioning, incremental loads, version control, and pipeline testing.
• Familiarity with streaming or event tooling such as Pub/Sub, Kafka, or Datastream; designing such systems from scratch is not required.
• Ability to take ownership of assigned delivery and operations, ask for architectural direction when needed, communicate risks early, and show curiosity about the logistics domain.

Nice to have

• Experience with OCR or document-parsing tools such as Tesseract or Textract, or with POs, invoices, and airway bills.
• Exposure to Terraform or Kubernetes.
• Prior logistics, supply chain, or B2B SaaS data experience.
• Exposure to ML, NLP, generative AI, forecasting, or analytics pipelines.

Culture & Benefits

• Hybrid work opportunities with flexibility to support diverse needs and lifestyles.
• Inclusive, international, and collaborative workplace focused on innovation, sustainability, and positive impact.
• Opportunity to grow ownership over time while working with senior engineers and a Lead Data Engineer.
• Work with AI-driven enterprise software and logistics data products used by customers worldwide.