Data Engineer II, Managed Operations Engineering & Data Science (MOEDS)

Amazon Development Center U.S., Inc. • Full-time • Herndon, Virginia, United States • $107.41k - $135.73k / year • 1d ago

DESCRIPTION

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!

Passionate about building, owning and operating massively scalable systems? Experienced in building and leading teams of highly competent software engineers? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.

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.

The Team: We're a small, innovative lab inside AWS working on reducing operational load and toil through long-term engineering projects.

Our Data Science & Data Engineering teams harness the power of data science to identify operational trends across AWS to inform high-value investment decisions for our development teams to eliminate operational toil.

This position requires that the candidate selected be a U.S. Citizen.

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Key job 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

A day in the life
Step into our state-of-the-art innovation lab within AWS, where we're pushing the boundaries of what's possible in cloud management. Our mission is to create a paradigm shift in operational efficiency through long-term engineering initiatives.

Join our Data Science & Data Engineering teams as we harness the full potential of advanced analytics, machine learning, and artificial intelligence. We're not just analyzing data – we're decoding the DNA of AWS operations to drive high-impact investment decisions and eliminate operational toil. The Data Engineering team is a critical component of this process, democratizing data, ensuring highly scalable and highly available solutions to serve our customers.

What we offer:

Advanced tech stack including the latest in big data technologies (AWS Glue, Apache Airflow, etc.), AI/ML, and cloud-native tools (CloudFormation, etc.).
Opportunity to work on projects that impact millions of AWS customers worldwide
Collaboration with some of the brightest minds in cloud computing and data science
Chance to shape the future of cloud operations and set new industry standards

About the team
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.

Utility Computing (UC)

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, and conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship and Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

BASIC QUALIFICATIONS

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

PREFERRED QUALIFICATIONS

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

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