Senior Data Engineer: AWS Data Lake & Serverless Warehouse

Amazon Data Services, Inc.; Seattle (WA); On-site; USD 140,000 - 210,000; Full time

Job summary

Amazon Data Services, Inc. in Seattle seeks a Senior Data Engineer to grow our Data Lake and Data Warehouse systems using serverless AWS components. You will own ETL pipelines, data modeling, and analytics infrastructure to enable internal customers to answer critical business questions with data.

You will work with Python, Spark, SQL and AWS services to build scalable data solutions, maintain security controls, and document data assets for teams across AWS.

Qualifications

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with SQL.
• Experience in at least one modern scripting or programming language.

Responsibilities

• Develop and maintain automated ETL pipelines (with monitoring) using Python/Spark and AWS services like S3, Glue, Lambda, SNS, SQS.
• Implement and support reporting and analytics infrastructure for internal business customers.
• Develop and maintain data security and permissions for enterprise-scale data warehouse and data lake, including encryption and access controls.
• Develop data objects for business analytics using data modeling techniques.
• Develop and optimize data warehouse and data lake tables with partitioning and performance best practices.
• Develop and maintain metadata, data catalog, and user documentation for internal customers.
• Collaborate with internal business customers and software teams to gather requirements for data publishing and consumption.

Skills

Data engineering

ETL pipelines

SQL

Python/Scala/Java

Mentoring

Tools

Hadoop

Hive

Spark

EMR

Job description

Amazon Data Services, Inc. in Seattle seeks a Senior Data Engineer to grow our Data Lake and Data Warehouse systems using serverless AWS components. You will own ETL pipelines, data modeling, and analytics infrastructure to enable internal customers to answer critical business questions with data.

You will work with Python, Spark, SQL and AWS services to build scalable data solutions, maintain security controls, and document data assets for teams across AWS.