onsite
Senior Data Engineer - Manufacturing - Amrize
Data Engineer
Lead end‑to‑end data engineering for manufacturing analytics, building scalable pipelines on AWS, optimizing Spark jobs, and designing robust data models to support real‑time insights across North America.
About the role
Key Responsibilities
- Design, develop, and maintain large‑scale data pipelines using Python, SQL, and Apache Spark on AWS.
- Implement and manage Airflow DAGs for automated data ingestion, transformation, and delivery to downstream analytics.
- Collaborate with data scientists and product teams to define data models, schemas, and governance standards.
- Optimize ETL processes for performance, reliability, and cost efficiency across cloud and on‑prem environments.
- Monitor pipeline health, troubleshoot issues, and continuously improve data quality and lineage.
Requirements
- 5+ years of experience in data engineering, preferably in manufacturing or industrial domains.
- Proficiency in Python, SQL, and Spark for large‑scale data processing.
- Hands‑on experience with AWS services (S3, Redshift, EMR, Glue, Lambda).
- Strong knowledge of data modeling, ETL best practices, and data governance.
- Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Skills
pythonsqlapache sparkawsairflow