Must-Have Skills & Experience:
- Strong hands-on experience as a Data Engineer .
- Strong proficiency in Python .
- Experience building and maintaining large-scale Apache Spark pipelines on AWS.
- Strong knowledge of the modern AWS Data Lake ecosystem , including:
- Amazon S3
- AWS Glue Data Catalog
- Amazon Athena
- Amazon EMR
- Amazon Redshift
- Experience designing and implementing reliable data ingestion, transformation, and validation pipelines at scale.
- Strong understanding of Data Lake architecture and best practices.
Differentiator / Preferred Experience:
- Hands-on experience with AWS Lake Formation permission models .
- Experience designing and testing:
- Row-level security
- Column-level filtering
- LF-TBAC (Tag-Based Access Control)
- Experience designing and validating end-to-end Data Lake permission models .
- Strong experience in test design, validation, and troubleshooting for large-scale data platforms and access-control models.
Data Engineer (Seattle) in seattle at Unknown Company
This position is listed as full time and onsite.