Senior Data Engineer, Parcels – Real-Time Logistics Data

Too Good To Go; København; Hybrid; DKK 900,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work Copenhagen HQ (4 days in‑p

Be part of a global B Corp

Impact on reducing food waste

Collaborative, values-driven team

Job summary

Too Good To Go is hiring a Data Engineer for the Parcels product domain in Copenhagen. You will be embedded with Product Managers, Tech Leads, and Engineers to design data pipelines and warehouse architecture for direct-to-consumer logistics and partner analytics.

You will work with Airflow, Python, dbt, Metaflow, and Terraform in a GitOps environment within a scale-up data platform. Hybrid work setup at Copenhagen HQ with strong focus on data quality and governance.

Qualifications

• Experience with logistics data or inventory systems (e.g., warehouse latency, logistics tracking, or order fulfillment).
• Strong Python and SQL skills; deep knowledge of data warehouse internals (AWS Redshift preferred).
• Experience with Airflow, dbt, and Infrastructure-as-Code (Terraform).

Responsibilities

• Design, build, and maintain real-time and batch data pipelines for logistics and inventory management.
• Drive automation to scale data solutions for high-growth supply chain features.
• Collaborate with Product Managers and Tech Leads to translate operational needs into robust requirements.
• Be the primary link between Parcels and the central Data Platform, balancing embedded work with platform standards.
• Ensure high data availability, low latency, and strong data governance across warehouse and logistics workflows.

Skills

Python

SQL

Airflow

dbt

Terraform

AWS Redshift

AWS Lambda

AWS Kinesis

AWS S3

Metaflow

GitHub Actions

Docker

Tools

Airflow

dbt

Metaflow

Terraform

AWS Redshift

AWS Lambda

AWS Kinesis

AWS S3

AWS Glue

Job description

Too Good To Go is hiring a Data Engineer for the Parcels product domain in Copenhagen. You will be embedded with Product Managers, Tech Leads, and Engineers to design data pipelines and warehouse architecture for direct-to-consumer logistics and partner analytics.

You will work with Airflow, Python, dbt, Metaflow, and Terraform in a GitOps environment within a scale-up data platform. Hybrid work setup at Copenhagen HQ with strong focus on data quality and governance.