Data Engineer II, Fire TV

Fire TV, Advertising and Appstore is reshaping the way millions of people discover, engage with, and enjoy entertainment every day. The FAA Decision Science organization is looking for a Data Engineer to help build scalable, reliable, and compliant data systems that support millions of customers worldwide.

This role contributes to the foundational data infrastructure used by Data Science, Business Intelligence, Product, Finance, Advertising, Engineering, and leadership teams to make high-quality business decisions. You will design, build, and operate data pipelines, data models, data quality mechanisms, and cloud-based infrastructure supporting Fire TV engagement, lifecycle analytics, Ads monetization, Appstore performance, executive reporting, forecasting, experimentation, and AI-enabled analytics.

This role is appropriate for an engineer who can independently own defined data systems or workstreams while partnering with senior engineers and cross-functional stakeholders on broader technical direction. You will be expected to work through moderate ambiguity, clarify requirements, make sound implementation trade-offs, improve operational reliability, and deliver scalable solutions that reduce manual effort over time. Successful engineers in this role improve reliability, automate recurring work, simplify data systems, document operational processes, and build trusted data products that help the business move faster.

Key job responsibilities Own the design, development, testing, deployment, and operation of data pipelines and datasets within an assigned domain

Build and maintain scalable ETL/ELT workflows using SQL, Python, AWS services, and big data technologies

Operate and improve data infrastructure, including Redshift clusters, data lake tables, orchestration workflows, monitoring, alerting, and data quality controls

Improve operational reliability by identifying recurring failures, reducing manual intervention, automating recovery steps, and creating clear runbooks

Partner with Data Science, Business Intelligence, Product, Finance, Engineering, Privacy, and Legal stakeholders to translate business and compliance requirements into scalable data solutions

Build and operate conversational, self-service, and agentic analytics data products

Support compliance, privacy, retention, and governance initiatives, including GDPR, DMA, telemetry migration, data access controls, and retention workflows

Contribute to data foundations that support forecasting, experimentation, ML/AI use cases, self-service analytics, and certified business metrics