Data Engineer II, Managed Operations Data Science (MODS)

Amazon•Arlington, VA

13d

About The Position

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions. As a Data Engineer, your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft AWS' strategic initiatives. In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across AWS to optimize growth, strategy, and user experience across AWS. Data Engineering: Guide teams in building optimal data artifacts (datasets, visualizations) to address key questions. Refine systems, design solutions, and create scalable data models. Ensure data security and quality while suggesting efficient architecture, development approaches, and data management standards for complex analytical problems. Product Leadership: Use data to identify opportunities, and tackle challenges. Ensure data artifacts/components deliver value by supporting AWS strategy and driving innovative solutions. Communication and Influence: Tell data-driven stories that convince and influence partners. Build credibility with clear insights, structured recommendations, and serve as a trusted partner within the organization. This role will sit in our new headquarters in Northern Virginia, where Amazon will invest $2.5 billion dollars, occupy 4 million square feet of energy efficient office space, and create at least 25,000 new full-time jobs. Our employees and the neighboring community will also benefit from the associated investments from the Commonwealth including infrastructure updates, public transportation improvements, and new access to Reagan National Airport. By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us. This position requires that the candidate selected be a U.S. Citizen. 10012

Requirements

3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Knowledge of distributed systems as it pertains to data storage and computing
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

Nice To Haves

5+ years of data engineering experience
Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Responsibilities

Collaboration and Product Development: Interact with business and software teams to understand their business requirements and operational processes, to inform system design
Data Modeling and Architecture: Develop robust data models and architectures that support the organization's data-driven initiatives, ensuring data quality, consistency, and accessibility.
Data Pipeline Development: Design, build, and maintain efficient, scalable, and reliable data pipelines to ingest, transform, and load data from various sources into a unified data platform.
Scalability and Performance: Design and implement scalable data solutions that can handle increasing data volumes and support high-performance data access and querying.
Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation