Project Kuiper is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.
Export Control : This position requires that the candidate selected be a U.S. Citizen in order to comply with U.S. government-imposed requirements related to the nature of the work and/or where it will be performed.
Kuiper Intelligence Data Services (KIDS) team is seeking a Senior Data Engineer who will help architect and build enterprise grade data platform, combining data lake and mesh architectures using latest AWS data services. In this role, you'll be responsible for building and maintaining the organization's central data platform that serves as the single source of truth, enabling teams across the company to develop analytics and dashboards. Working closely with cross-functional teams across hardware, software, supply chain, manufacturing, launch, facilities, finance, compliance, and HR, you'll implement sophisticated data architectures to support various analytics use cases including business reporting, production pipelines, optimization models, statistical analysis, and simulations.
As a Sr Data Engineer, you will be responsible for architecture and engineering of data infrastructure across our systems of supply chain, development, production and test. You'll drive production optimization by managing data stores, developing key performance indicators, and enabling data-driven program decisions. The role focuses on architecting and implementing data ingestion processes that provide crucial insights into our business health, ultimately serving as the foundation for our organization's data-driven future. Strong expertise in AWS data services and experience with enterprise-scale data architectures is essential for success in this position.
The ideal candidate is a technically savvy engineer maintaining strong ownership, detail-oriented analytical thinker, communicates effectively with both technical and business teams and thrives in a fast-paced agile environment. They combine strong technical expertise with business acumen, can manage multiple priorities, and adapts quickly to changing requirements and priorities.
Key job responsibilities
- Design, implement and maintain data infrastructure including data modeling, ETL pipelines, and ongoing maintenance.
- Partner with product, operational, and technical teams to build data pipelines from a wide variety of sources using AWS big data technologies (Lake Formation, Glue, S3, MWAA, Lambda, etc.).
- Build a data dictionary, catalog and governance plan and manage and audit all of the registered data via robust mechanisms.
- Work with data consumers to provide and correlate the right data for business intelligence and machine learning use-cases.
- Develop automated solutions to minimize manual processes with focus on efficiency and scalability.
- Provide guidance on data stewardship for teams onboarding to the central data systems.
A day in the life
As a Senior Data Engineer, you'll start your day collaborating with cross-functional partners to understand their data needs. You might spend time optimizing ETL pipelines, reviewing code with team members, or designing new data models. Yow will work with partner teams on building golden datasets. You'll participate in technical discussions to solve complex problems and mentor junior team members.
About the team
KIDS team owns DataHive, a centralized data and analytics infrastructure that serves as the single source of truth, enabling teams to develop dashboards and insights that drive Kuiper's satellite production operations. The platform enforces robust data governance with tagging and access controls, enhancing data discoverability and security. KIDS offers self-serve capabilities for both data providers and consumers, including features including data quality monitoring, automated and manual data tagging, and the ability to bring in custom data tables.
