Data Engineer II, AAE

Amazon • Bellevue, WA

4d • $132,100 - $178,800 • Onsite

About The Position

AWS AI Services is one of the largest and fastest-growing business units within AWS, powering services like Amazon Bedrock, AgentCore, QuickSight, Q Business, Kendra, and Kiro. Our Data Engineering team builds the intelligence infrastructure that makes this portfolio measurable — from revenue attribution and launch telemetry to agent-generated business reviews that serve VP-level leadership weekly. We are looking for an experienced, self-driven Data Engineer to join a team that operates at the intersection of data engineering and agentic AI. In this role, you won't just build pipelines — you'll design data platforms that power AI agents, build automated reporting systems that replace manual processes, and create the data foundations that prove business impact across a multi-billion dollar service portfolio. You'll work with modern AWS-native data stacks (Glue, Redshift, Athena, QuickSight, Bedrock, SageMaker), build event-driven architectures with CDK, and contribute to agentic workflows that generate executive-level insights autonomously. You should be comfortable operating in ambiguity, designing data models from scratch for new services, and making architectural trade-off decisions that scale. This is a high-visibility role. Your work will directly inform decisions made by VPs, GMs, and the CFO's office — from revenue unification mandates to enterprise deal velocity to AI adoption measurement.

Requirements

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

Nice To Haves

• 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 providing technical leadership and mentoring other engineers for best practices on data engineering

Responsibilities

• Design and build end-to-end data platforms for new AWS AI services — defining schemas, data models, ETL pipelines, and analytics infrastructure where none exists today
• Build and maintain production ETL/ELT pipelines using AWS Glue, Airflow, Spark, and Python to source data from operational, commercial, and telemetry systems into unified data models
• Develop agentic data workflows — automated reporting pipelines that leverage AI/ML to generate business insights, WBR summaries, and anomaly detection without manual intervention
• Create event-driven data architectures using CDK, Lambda, SNS/SQS, and S3 event notifications to support real-time data ingestion and processing
• Build executive dashboards and self-serve analytics using QuickSight that serve VP/GM-level leadership across multiple service lines
• Own revenue data accuracy — implement and validate 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 Managers, Finance, Service Engineering, GTM, and Data Science teams to translate business questions into scalable data solutions
• Optimize pipeline performance — reduce runtimes, eliminate redundant processing, and improve SLA compliance across production workloads
• Mentor engineers, contribute to team standards, and drive a culture of automation, code quality, and operational excellence

Benefits

• sign-on payments
• restricted stock units (RSUs)
• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed