Summary
We are seeking a Senior Data Engineer to join a logistics data and machine learning platform team. You will design and build real-time data pipelines using Apache Kafka and develop CDC-based ingestion pipelines with Debezium on GCP and BigQuery. You will ensure data quality and observability, partner with data scientists to operationalize ML workflows, and support a high-scale logistics domain. Participation in a flexible on-call rotation is required.
Highlights
Work on high-scale real-time data pipelines and AI-driven logistics. Tackle high-impact challenges in last-mile delivery. Collaborative and positive team environment.
Description
Job DescriptionWe are looking for a Senior Data Engineer to join the Logistics Data & Machine Learning Platform team on our journey to always deliver amazing experiences.
At Delivery Hero, we are building the next generation of logistics intelligence powered by real-time data and AI.
Our Logistics Data Engineering team sits at the core of this transformation - enabling high-scale data pipelines, powering advanced analytics, and accelerating AI-driven products across the organization.
In our Logistics Team, you’ll tackle high-impact challenges that make last-mile delivery efficient, affordable, and sustainable.
Your work will directly improve experiences for riders, end customers, and merchants across the globe.
Each enhancement you contribute will help Delivery Hero optimize delivery operations, supporting expansion into new areas like grocery and retail.
We are looking for someone to design, build, and scale robust data systems that fuel real-time decision-making and innovation across logistics.
Design and build real-time data pipelines using Apache Kafka to enable event-driven architectures and real-time analytics across global logistics platforms.
Develop CDC-based ingestion pipelines with Debezium, focusing on core infrastructure engineering and high-scale integration with GCP and BigQuery.
Drive a mission-critical initiative to ensure high standards for data quality, observability, and reliability, creating a stable foundation for the team’s AI-powered workflows.
Partner with data scientists and ML engineers to operationalize workflows, building the scalable data models required for logistics optimization and experimentation.
Support the logistics domain with reliable, well-documented datasets while bringing a positive, collaborative energy to a close-knit, high-impact platform team.
Maintain world-class infrastructure by participating in a flexible on-call rotation, ensuring the stability of the moving pieces within our logistics and pricing systems.