Data Engineer Ii, Data Management Team

Amazon Amazon · Big Tech · Herndon, VA · Operations, IT, & Support Engineering

Data Engineer II for AWS Public Sector team, focusing on building and managing big data systems, data pipelines, and infrastructure for analytics and reporting. Collaborates with ML engineers and BI engineers.

What you'd actually do

  1. Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations.
  2. Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.
  3. Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
  4. Implementing data structures using best practices in data modeling to provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.
  5. Evaluating and making decisions around dataset implementations designed and proposed by peer data engineers. Mentor junior data engineers.

Skills

Required

  • 3+ years of data engineering experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience

Nice to have

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)