Data Engineer II, AAE

Based in Bellevue, WA onsite, this Data Engineer II role focuses on building end-to-end data platforms for AWS AI services and delivering executive insights through automated analytics and revenue reporting.

Responsibilities

• Architect and implement complete data platforms for new AWS AI services, establishing schemas, data models, ETL/ELT pipelines, and analytics infrastructure where none exists today
• Develop and maintain production ETL/ELT pipelines with AWS Glue, Airflow, Spark, and Python to ingest data from operational, commercial, and telemetry sources into unified data models
• Create agentic data workflows featuring automated reporting pipelines that leverage AI/ML to generate business insights, weekly business review summaries, and anomaly detection with minimal manual intervention
• Build event-driven data architectures using CDK, Lambda, SNS/SQS, and S3 event notifications to support real-time data ingestion and processing
• Develop executive dashboards and self-serve analytics using QuickSight for VP/GM-level leadership across multiple service lines
• Ensure revenue data accuracy by implementing and validating revenue attribution models, discount calculations, and financial data pipelines that feed CFO-mandated reporting
• Design data models that support both operational analytics (feature adoption, customer health, churn signals) and financial reporting (revenue, billing, forecasting)
• Collaborate with Product Management, Finance, Service Engineering, GTM, and Data Science teams to translate business questions into scalable data solutions
• Optimize pipeline performance by reducing runtimes, eliminating redundant processing, and improving SLA compliance across production workloads
• Mentor engineers, contribute to team standards, and foster a culture of automation, code quality, and operational excellence

Requirements

• 5+ years of data engineering experience
• 3+ years of developing and operating large-scale BI data structures for analytics using ETL/ELT processes
• 3+ years of developing and operating large-scale BI data structures for analytics using data modeling
• Experience with data modeling, data warehousing, and building ETL pipelines

Technologies

• AWS Glue
• Redshift
• Athena
• QuickSight
• Bedrock
• SageMaker
• CDK
• Lambda
• SNS
• SQS
• S3
• Airflow
• Spark
• Python
• Kendra
• Kiro

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, 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
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)

A day in the life

• Design data models for newly launched AWS AI services and deploy ETL pipelines to onboard telemetry and revenue data
• Validate data accuracy across financial reporting systems
• Architect CDK-based event-driven pipelines and collaborate with Product Managers to define launch metrics
• Resolve data discrepancies surfaced by Finance and optimize production queries feeding VP-level weekly business reviews

About the team

The AI Services Data Engineering team builds the data infrastructure behind AWS Armored AI products including Bedrock, AgentCore, QuickSight, Q Business, Kendra, Kiro, and Transform. Our data powers metrics and reporting that inform executive visibility into Agentic AI revenue, adoption, and growth, including automated weekly business reviews with agent-generated summaries and revenue attribution models for multi-billion dollar pricing programs and launch telemetry.