AmazonPosted 1w ago

Data Engineer, Leo Global Business and Customer Operations

Data Engineer, Leo Global Business and Customer Operations at Amazon scores 25 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

US, VA, Arlingtonmidfull-time$132k-$179k

AI in this role

Build and maintain data infrastructure and pipelines supporting general analytics and GenAI tools for Amazon Leo.

awssalesforcemarketo

data-engineeringdata-pipelinesetlsql

Amazon Leo is Amazon's low Earth orbit (LEO) satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks — from individual households to schools, hospitals, businesses, and government agencies operating in locations without reliable connectivity.

Join us as we build the data and science backbone for Leo's entire organization. As a central team, we establish the infrastructure, analytics capabilities, and generative artificial intelligence (GenAI)-powered tools that enable every Leo team — from business operations to customer support to capacity planning — to make data-driven decisions and deliver exceptional customer experiences.

As a Data Engineer, you will build and own the pipelines that power Leo's data platform. You will design, implement, and maintain the data infrastructure that ingests from dozens of source systems, enforce quality standards that teams rely on for business decisions, and drive operational efficiencies that allow Leo to scale. Your work directly enables the launch and global growth of a rapidly scaling satellite business.

Key job responsibilities
In this role, you will:
- Data Pipeline Development: Build, maintain, and scale data pipelines that ingest data from first-party (Leo catalog, order management), second-party (Amazon Web Services (AWS) services), and third-party sources (Salesforce, Marketo) into a unified data lake. Ensure pipelines are reliable, fault-tolerant, and meet cross-organizational needs.
- Data Quality and Governance: Define and implement data quality checks, validation frameworks, and monitoring alerts. Establish standards for data accuracy, completeness, and consistency. Partner with consuming teams to resolve data issues and enforce governance protocols.
- Operational Efficiency: Identify and eliminate bottlenecks in data workflows. Automate manual processes, reduce pipeline latency, and improve cost efficiency of data storage and compute. Track and report on pipeline health and SLA (Service Level Agreement) adherence.
- Cross-Team Partnership: Collaborate with business operations, data science, and engineering teams to understand data needs and deliver curated, reliable datasets. Contribute to shared dashboards, standardized metrics, and centralized tooling.
- Infrastructure Standards: Apply security best practices and compliance requirements to data systems. Support multi-tenancy requirements and contribute to the adoption of centralized data platforms.

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.

About the team
Within Global Business and Customer Operations, our team sits centrally as the primary Data Infrastructure and Core Data services org powering Leo Business decisions worldwide. We are a cross-functional team of data/business intelligence engineers and data/research/applied scientists, ensuring that global technical and non-technical data needs are met through traditional and GenAI channels.

Basic qualifications

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, VA, Arlington - 132,100.00 - 178,800.00 USD annually

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Skills and AI tools this role asks for

Data EngineeringData PipelinesEtlSqlAwsSalesforceMarketo

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
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Tell me about a project where sql was part of your work. What did you do?
Walk me through how you've used Aws in your day-to-day work.

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