Data Engineer, Leo Global Business and Customer Operations

Amazon is building Amazon Leo, a low Earth orbit satellite network that provides reliable internet connectivity to customers beyond the reach of existing networks. The Data Engineer will build and own data pipelines and infrastructure for Leo's data platform, ensuring data quality, governance, operational efficiency, and reliable datasets for business operations, data science, and engineering teams.

Responsibilities

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

Preferred

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

AWS

Amazon Redshift

Amazon S3

AWS Glue

Amazon EMR

Amazon Kinesis

Kinesis Firehose

AWS Lambda

IAM roles

IAM permissions

Non-relational databases

Object storage

Document stores

Key-value stores

Graph databases

Column-family databases

Data warehouse architecture

Infrastructure components

ETL

ELT

Reporting tools

Analytic tools

Data environments

Data structures

SQL coding

Benefits

Sign-on payments

Restricted stock units (RSUs)

Health insurance, including medical, dental, vision, prescription, Basic Life & AD&D insurance, and an option for Supplemental life plans

Employee Assistance Program (EAP)

Mental Health Support

Medical Advice Line

Flexible Spending Accounts

Adoption and Surrogacy Reimbursement coverage

401(k) matching

Paid time off

Parental leave

Company

Online retail and cloud computing services

Seattle, Washington, USA

https://amazon.com/

Founded in 1994

10001+ employees

Qualifications

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

3+ years of data engineering experience

Experience with data modeling, warehousing and building ETL pipelines

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

Required skills

Data Modeling, Data Warehousing, ETL/ELT Pipelines, SQL, Amazon Redshift, Amazon S3, AWS Glue, Amazon EMR, Amazon Kinesis, AWS Lambda, AWS IAM, Non-Relational Databases

Experience

3+ years