Alexa Sensitive Content Intelligence team leverages natural language understanding, machine learning, and big data to help Alexa identify sensitive content. We're seeking an exceptional Data Engineer to join our Data Engineering team, where you'll architect and build data systems that power Amazon's Devices content moderation data warehouse and reporting pipeline. This role combines technical expertise with business acumen to transform complex data into actionable insights.
You'll be instrumental in building the next generation of data-driven tools that highlight and protect bad content being exposed to customers on Amazon's Devices including Alexa+. You should have experience with real-time data processing, high-throughput systems, and end-to-end platform development. Knowledge of modern data engineering tools and technologies is essential.
The ideal candidate combines technical excellence with strategic thinking, bringing both the ability to architect complex systems and the vision to drive innovation in technology.

Core Responsibilities:

Contribute to the architecture, design and implementation of next generation BI solutions – including streaming data applications.
Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
Collaborate with data scientists, BIEs to deliver high quality data architecture and pipelines.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

Basic Qualifications:

Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
Industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
Experience working with AWS big data technologies (EMR, Redshift, S3, AWS Glue, Kinesis and Lambda for Serverless ETL)
Knowledge of data management fundamentals and data storage principles
Knowledge of distributed systems as it pertains to data storage and computing
Hands-on experience and advanced knowledge of SQL
Basic scripting skills using Python and Scala

Basic understanding of Machine Learning:

• Key job responsibilities
• Design and implement scalable data infrastructure.
• Develop robust data pipelines and analytics processes that enable real-time decision making
• Collaborate with Science, software engineers, and product managers to deliver reliable data solutions
• Lead technical initiatives and mentor team members in best practices for data engineering
• Create automated systems to replace manual processes and support global expansion
  A day in the life
  As a member of the team you will be responsible for design, development and launch of new features. You will be required to participate with other senior engineers and peers in developing the overall system architecture, contribute the review of design and code of peer engineers and mentor freshers/junior engineers. You will also work on high availability, security compliance and maintenance of our existing services.

Basic Qualifications

• 3+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, 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)
  Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.