Amazon
Data Engineer, Network Design Analytics
Amazon, Seattle, Washington, us, 98127
Embrace the unique opportunity to join Amazon's Network Design team as a Data Engineer, where you won't just be working on projects; you'll be building big, innovative solutions that drive our ability to deliver billions of shipments each year. This role offers the chance to work with leading-edge technologies and directly impact our business on a global scale. Additionally, it provides a platform for immense professional growth and career development. Here's why you will love working with us:
Take ownership of significant projects, driving them from conception to completion Learn and grow rapidly, developing skills that will propel your career forward Collaborate with a team of innovative thinkers, always pushing boundaries Use cutting-edge technologies and methodologies to solve complex, real-world problems Contribute directly to a mission that affects billions of customers worldwide
Key job responsibilities
As our Data Engineer, you will:
Design and manage data pipelines using AWS infrastructure Develop robust code in a fast-paced DevOps environment Use Python, Java, TypeScript, and SQL to create and optimize solutions Continuously streamline and automate reporting and analytical processes Work jointly with your teammates, communicating effectively
A day in the life
You'll start your day with a quick catch-up to set priorities and tackle challenges. From there, you might deep-dive into raw data, discuss and review the design of a new data pipeline, or optimize an existing one using AWS services. You will regularly interact with teammates to align on expectations, report on progress, and brainstorm new solutions. Every day brings a new challenge that will require your analytical skills, technical expertise, and innovative thinking.
About the team
Network Design Analytics is a diverse group of engineers, strategists, and innovators. Our mission is to design and develop systems that scale Amazon's decision-making processes through automation. We have profiles of Business Intelligence, Data Science, Applied Science, and Data Engineering. We embrace a culture of learning, collaboration, and innovation, constantly pushing boundaries to deliver the best solutions.
Minimum Qualifications
- Experience in data engineering - Experience with data modeling, warehousing, and building ETL pipelines - Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting languages (e.g., Python, KornShell) - 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 opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use, and transfer the personal data of our candidates.
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Take ownership of significant projects, driving them from conception to completion Learn and grow rapidly, developing skills that will propel your career forward Collaborate with a team of innovative thinkers, always pushing boundaries Use cutting-edge technologies and methodologies to solve complex, real-world problems Contribute directly to a mission that affects billions of customers worldwide
Key job responsibilities
As our Data Engineer, you will:
Design and manage data pipelines using AWS infrastructure Develop robust code in a fast-paced DevOps environment Use Python, Java, TypeScript, and SQL to create and optimize solutions Continuously streamline and automate reporting and analytical processes Work jointly with your teammates, communicating effectively
A day in the life
You'll start your day with a quick catch-up to set priorities and tackle challenges. From there, you might deep-dive into raw data, discuss and review the design of a new data pipeline, or optimize an existing one using AWS services. You will regularly interact with teammates to align on expectations, report on progress, and brainstorm new solutions. Every day brings a new challenge that will require your analytical skills, technical expertise, and innovative thinking.
About the team
Network Design Analytics is a diverse group of engineers, strategists, and innovators. Our mission is to design and develop systems that scale Amazon's decision-making processes through automation. We have profiles of Business Intelligence, Data Science, Applied Science, and Data Engineering. We embrace a culture of learning, collaboration, and innovation, constantly pushing boundaries to deliver the best solutions.
Minimum Qualifications
- Experience in data engineering - Experience with data modeling, warehousing, and building ETL pipelines - Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting languages (e.g., Python, KornShell) - 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 opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use, and transfer the personal data of our candidates.
#J-18808-Ljbffr