Sr. Data Engineer, Leo ProdOps, Project Leo
Job ID: 3094828 | Amazon Kuiper Manufacturing Enterprises LLC
Amazon Leo 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 Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
As a Sr. Data Engineer (DE) you will design, architect, and manage scalable data infrastructure that directly empowers our science team and initiatives. You will own the full data lifecycle, building and maintaining robust, high‑quality data pipelines and feature stores required for developing and deploying production‑grade ML models. This role involves significant hands‑on engineering to transform raw data from complex systems into reliable, accessible data products, providing the essential foundation for advanced analytics, predictive modeling, and strategic decision‑making across Leo’s Production Operations. You will have direct responsibility for the architecture and engineering of data infrastructure across our systems to support key scientific areas like Statistical Process Control (SPC), time series analysis, supply chain optimization, and production testing.
As a Sr. Data Engineer within LeoProdOps, you will demonstrate technical leadership by creating clarity out of ambiguity and enabling productive collaboration. You are a customer‑obsessed problem‑solver who partners effectively with peers across all Leo teams, including hardware, software, supply chain, manufacturing, launch, facilities, and finance. Your ability to invent and simplify will be key to solving technical challenges, and you will have the opportunity to pioneer ML and GenAI‑powered data solutions that improve analytics efficiency and uncover hidden patterns. You will use your communication skills to articulate complex data concepts, manage expectations, and drive consensus across diverse technical and non‑technical stakeholders.
Key job responsibilities

Architect and implement the next‑generation data systems for Leo Production Operations
Improve existing solutions and drive the evolution of scaling our infrastructure to support science and ML workloads
Work with engineers and scientists to build and manage feature stores for consistent definition, storage, and retrieval of data features for both model training and real‑time inference
Develop and optimize data pipelines and data models to ensure data integrity and efficient access for analyses
Implement data quality checks, validation, and monitoring to ensure reliable consistent data for all consumers
Maintain core data tools and documentation (data warehouse, metadata, data catalog) to enable self‑service reporting for customers
Support production optimization by managing data stores and tracking KPIs to enable data‑driven program decisions
Provide technical and thought leadership for Data Engineering and Business Intelligence, mentoring peers and driving data best practices across Leo
Convey complex ideas in simple terms to both technical and non‑technical audiences, using clear written and verbal communication

A day in the life
This role will be highly collaborative, requiring partnerships with cross‑functional leaders to drive positive results. You will tackle challenging, novel business problems every day and have the opportunity to work with multiple technical teams across Leo.
You will work on built data infrastructure and enable development of tools for Leo’s production teams that will help streamline the production of our satellite technology.
You should relish the idea of solving problems that haven’t been solved at scale before. Along the way, we guarantee that you will learn a lot, have fun and make a positive impact on millions of people.
Basic Qualifications

Bachelor’s degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
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 with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy

Preferred Qualifications

Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Experience operating large data warehouses
Knowledge of data mining techniques, predictive analytics, and statistical modeling
Strong ability to interact, communicate, present, and influence within multiple levels of the organization

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job‑related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign‑on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
This position will remain posted until filled. Applicants should apply via our internal or external career site.
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