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Senior Data Engineer - Syngenta
Data Engineer
Senior Data Engineer leading design and implementation of scalable data pipelines and analytics platforms using Python, Spark, SQL, and AWS services.
About the role
Key Responsibilities
- Design, develop, and maintain high‑performance data pipelines for ingesting, transforming, and loading large agricultural datasets.
- Build and optimize data models and warehouses to support analytics, reporting, and machine‑learning use cases.
- Implement orchestration workflows with Apache Airflow and ensure reliable scheduling, monitoring, and error handling.
- Leverage AWS services (e.g., S3, Redshift, Glue, EMR) to create scalable, secure, and cost‑effective data solutions.
- Collaborate with data scientists, product owners, and domain experts to translate business requirements into technical specifications.
Requirements
- 5+ years of professional experience in data engineering or related fields.
- Strong proficiency in Python and SQL, with hands‑on experience in Apache Spark or similar distributed processing frameworks.
- Deep understanding of cloud platforms, particularly AWS, and services for data storage and processing.
- Experience building ETL pipelines and workflow orchestration using tools such as Apache Airflow.
- Solid knowledge of data modeling, data warehousing concepts, and best practices for data quality and governance.
Skills
pythonsqlapache sparkaws