Data Engineer II, AAE

Amazon

Bellevue, WA

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JOB DETAILS

SKILLS

AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Architectural Services, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Automation, Best Practices, Billing, Business Growth, Business Intelligence, Cadence, Customer Acquisition, Customer Churn, Data Cleaning, Data Management, Data Modeling, Data Quality, Data Science, Data Structures, Data Warehousing, Database Extract Transform and Load (ETL), Electronic Medical Records, Engineering, Finance, Financial Management, Financial Reporting, Financial Systems, Forecasting, Head of Finance, Leadership, Mentoring, Metrics, Model Validation, Operational Audit, Operational Support, Performance Tuning/Optimization, Pricing, Product/Service Launch, Python Programming/Scripting Language, Query Optimization, Relational Databases (RDBMS), Reporting Dashboards, Revenue Growth, Revenue/Sales Reporting, Service Level Agreement (SLA), Simple Queue Service (SQS), Technical Leadership, Telemetry

LOCATION

Bellevue, WA

POSTED

30+ days ago

Description 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. Key job 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 A day in the life As a Data Engineer on this team, you will design data models for newly launched AWS AI services, build and deploy ETL pipelines to onboard telemetry and revenue data, and validate data accuracy across financial reporting systems. On any given day, you may be architecting a CDK-based event-driven pipeline, collaborating with Product Managers to define launch metrics, resolving data discrepancies surfaced by Finance, or optimizing production queries that feed into VP-level weekly business reviews. Your deliverables ship to production on a regular cadence and are consumed directly by senior leadership for strategic decision-making. About the team The AI Services Data Engineering team builds the data infrastructure behind AWS's Agentic AI portfolio - Amazon Bedrock, AgentCore, QuickSight, Q Business, Kendra, Kiro, and Transform. Our data powers the metrics and reporting that flow up to Amazon's CEO and CFO, supporting S-Team level visibility into Agentic AI revenue, adoption, and growth. We build automated WBR reporting with agent-generated summaries, revenue attribution models for multi-billion dollar pricing programs, and launch telemetry platforms for new GA services. We ship weekly, operate across multiple VP orgs, and value automation over manual work, clean data models over quick fixes, and engineers who own their domain end-to-end. Basic Qualifications - 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 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 providing technical leadership and mentoring other engineers for best practices on data engineering 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, WA, Bellevue - 132,100.00 - 178,800.00 USD annually

About the Company

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

COMPANY SIZE

10,000 employees or more

INDUSTRY

Other/Not Classified

FOUNDED

1994

WEBSITE

http://Amazon.com/militaryroles

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