Amazon - Arlington, VA

posted 2 months ago

Full-time - Mid Level
Arlington, VA
Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

As a Senior Data Engineer at Amazon, you will be at the forefront of leveraging data to deliver actionable insights that significantly impact daily business decisions. This role is designed for individuals who are excited about working with massive volumes of data and building a cutting-edge, highly scalable analytics platform using AWS technologies. Engineers at Amazon tackle real-world problems on a global scale, taking ownership of their systems from end-to-end and influencing the direction of technology that affects hundreds of millions of customers worldwide. You will join a team of intelligent, customer-obsessed developers who think big and enjoy their work. In this position, you will be responsible for creating backend systems that scale by utilizing Aurora Serverless and NoSQL databases like DynamoDB. You will build and maintain ETL processes that ensure our data warehouse is updated with accurate information. Additionally, you will manage the ingestion and processing of event stream data from various source systems and maintain Managed Apache Airflow workflows that transform and move data between source systems and a data lake. Your role will also involve writing scripts and queries to select and parse data in response to requests from customers and leadership, while continuously raising the bar on quality, security, performance, scalability, usability, and operations. The ideal candidate will possess excellent business and communication skills, enabling them to work effectively with business owners to develop and define key business questions. Collaboration with Software Developers and Technical Program Managers will be essential to analyze data that answers these questions. A solid understanding of building efficient and scalable data infrastructure and data models is crucial for success in this role. You will be part of a team that works on tooling that aids in building and deploying services to every AWS region globally, with opportunities to work on highly visible projects that directly impact numerous other teams at Amazon. This team is tasked with transforming how AWS builds new regions by leveraging data and automation to optimize region builds, ultimately finding insights that reduce the duration of AWS region builds.

Responsibilities

  • Create backend systems that scale by leveraging Aurora Serverless and NoSQL databases (DynamoDB).
  • Build and maintain the ETL's responsible for keeping our data warehouse up-to-date with accurate information.
  • Manage the ingestion and processing of event stream data from multiple source systems.
  • Maintain Managed Apache Airflow workflows transforming and moving data between source systems and a data lake.
  • Write scripts and queries to select and parse data in response to customer and leadership requests.
  • Raise the bar on quality, security, performance, scalability, usability and operations.
  • Support the Region Services organization mission through the creation of tooling for AWS region builds, service expansion and feature tracking.

Requirements

  • 5+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience mentoring team members on best practices.

Nice-to-haves

  • Experience operating large data warehouses
  • Bachelor's degree
  • 7+ years of data engineering, database engineering, business intelligence or business analytics experience
  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Knowledge of distributed systems as it pertains to data storage and computing
  • Experience with big data technologies such as: RDS, Athena, S3, Redshift, Glue, Airflow, etc.

Benefits

  • Health insurance
  • 401k
  • Paid holidays
  • Flexible scheduling
  • Professional development opportunities
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