Amazon
Data Engineer, AWS Infrastructure Supply Chain Automation
Amazon, Herndon, Virginia, United States, 22070
Data Engineer, AWS Infrastructure Supply Chain Automation
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We’re looking for a Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! Our Data Engineers build the ETL and analytics solutions for our internal customers to answer questions with data and drive critical improvements for the business. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. Key Responsibilities: Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS. Implement and support reporting and analytics infrastructure for internal business customers. Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging. Develop data objects for business analytics using data modeling techniques. Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization. Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers. Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions. About the Team: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Basic Qualifications
3+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Bachelor's degree in Computer Science, Software Engineering, Information Technology, Mathematics, or related technical field Preferred Qualifications
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) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. https://amazon.jobs/content/en/how-we-hire/accommodations for more information. #J-18808-Ljbffr
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We’re looking for a Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! Our Data Engineers build the ETL and analytics solutions for our internal customers to answer questions with data and drive critical improvements for the business. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. Key Responsibilities: Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS. Implement and support reporting and analytics infrastructure for internal business customers. Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging. Develop data objects for business analytics using data modeling techniques. Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization. Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers. Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions. About the Team: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Basic Qualifications
3+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Bachelor's degree in Computer Science, Software Engineering, Information Technology, Mathematics, or related technical field Preferred Qualifications
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) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. https://amazon.jobs/content/en/how-we-hire/accommodations for more information. #J-18808-Ljbffr