Design, build, and scale robust data solutions that power global logistics, supply chain visibility, and operational intelligence
Job Summary
Design, build, and scale robust data solutions that power global logistics, supply chain visibility, and operational intelligence.
Architect and implement cloud-native data platforms using modern data stack technologies, ensuring data quality, lineage, observability, and governance best practices.
Collaborate closely with product managers, data scientists, analysts, and cross-functional engineering teams to deliver scalable and resilient data products that drive business impact.
Matching Summary
Design, build, and scale robust data solutions that power global logistics, supply chain visibility, and operational intelligence.
Skills & Requirements
Must-have
Python, SQL, and Spark proficiency
Cloud platforms (Azure / AWS / GCP)
Data orchestration tools (Airflow, ADF)
Data warehouses/lakehouses (Snowflake, Databricks, BigQuery)
Distributed systems and large-scale datasets
Nice-to-have
Logistics or supply chain experience
Streaming technologies (Kafka, Event Hubs)
DevOps practices and Infrastructure-as-Code
AI/ML data pipelines support
Continuous learning and innovation
Key Requirements
6–10 years of experience in data engineering
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Strong understanding of data modeling (star schema, dimensional modeling)