Senior Data Engineer Seattle AWS Spark Airflow Python
Overview
Design and lead scalable data pipelines for enterprise analytics. Own development of ETL processes using Python and Spark. Scale infrastructure on AWS. Drive improvements in data quality and performance. This role differs by focusing on cloud-native architecture and cross-functional leadership.
What You'll Do8
- 1Build robust ETL pipelines using Python and Spark
- 2Design and implement scalable data architectures on AWS
- 3Lead Kubernetes clusters for data processing workloads
- 4Optimize data workflows using Airflow orchestration
- 5Ship production-grade solutions within 90 days
- 6Drive automation and debugging of complex systems
- 7Collaborate with stakeholders to define technical requirements
- 8Mentor junior engineers and foster best practices
Requirements5
- 15+ years building ETL pipelines with Python and Spark
- 23-5 seasons managing AWS environments
- 35+ years experience with Kubernetes and Airflow
- 4Expertise in AWS services and data engineering
- 5Strong understanding of data pipeline optimization techniques
Salary Insight
Salary not disclosed in listing
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