Role at a glance
- Salary
- $99.5K – $160K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 3+ years of experience in business intelligence, data engineering, or analytics engineering
- Education
- Bachelor's, Master's
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Business Intelligence Engineer will join the EC2 + Networking Product BI team within AWS Analytics & Engineering and own end-to-end analytics for one or more Compute service areas. The role supports executive reporting, service-performance measurement, product analysis, and dashboards for AWS Compute product families.
What You'll Do
- Build, monitor, and operate ETL pipelines serving executive-facing reports.
- Deliver Weekly and Daily Business Review reporting for EC2 services to senior stakeholders.
- Generate callouts on service performance, including trends, anomalies, and key drivers.
- Ingest data sources and create metrics tracking usage, capacity, adoption, and customer growth.
- Conduct deep-dive analyses for Product Managers, Sales, and Finance teams.
- Design, build, and maintain interactive dashboards covering product trends, customer growth, instance utilization, and feature adoption.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- Bachelor's degree in engineering, statistics, computer science, mathematics, or a related quantitative field
- 3+ years of experience in business intelligence, data engineering, or analytics engineering
- Proficiency in SQL with experience writing complex queries against large-scale data warehouses (Redshift, Spark, or equivalent)
- Experience with at least one programming language (Python, R, or Java) for data manipulation and analysis
- Experience building and maintaining ETL/ELT data pipelines
- Experience designing and publishing BI dashboards (QuickSight, Tableau, or equivalent)
Preferred
- Master's degree in a quantitative field
- Experience with AI/ML technologies, including large language models (LLMs) and building automation workflows
- Experience with AWS services (Redshift, S3, Lambda, Glue, SageMaker, Bedrock)
- Experience building self-serve analytics platforms or data products
- Strong data storytelling skills — ability to present complex analyses to senior leadership
- Experience working with Product Management teams in a cloud computing or SaaS environment
- Familiarity with orchestration frameworks (Airflow, Step Functions, or similar workflow engines)
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Key job responsibilities
• ETL Monitoring & Pipeline Operations: Own the reliability and timeliness of 200+ data pipelines serving executive-facing reports. Today, the team uses automated alarms for real-time monitoring and AI-powered agents that self-heal failures and triage tasks — you will maintain and extend this system using Redshift, orchestration frameworks, and AWS data services.
• Report Delivery & Business Reviews: Own and operate Weekly/Daily Business Review (WBR/DBR) reporting for EC2 services, ensuring accurate, timely delivery to CEO/S-Team and VP-level stakeholders. Today, report generation, validation, and delivery are automated via LLMs — you will operate and improve these workflows.
• Callout Generation: Generate callouts on service performance — identifying week-over-week trends, anomalies, and key drivers to surface in executive reviews. Today, callout generation across all 9 services is LLM-automated — you will own the quality bar and continuously improve prompt and pipeline accuracy.
• Data Ingestion & Metric Creation: Ingest new data sources and build metrics that track business health (usage, capacity, adoption, customer growth). Today, the team maintains scalable ETL pipelines in Redshift with workflow orchestration — you will ensure metrics remain sustainable, reproducible, and available on demand.
• Analysis & Deep Dives: Conduct deep-dive analyses for Product Managers, Sales, and Finance teams. Today, the team uses a proprietary analytics platform with governed SOPs, stored context, and pre-built queries — enabling any stakeholder to deep-dive with technical depth and reproducibility. You will author and maintain these SOPs and analyses.
• Dashboard Development: Design, build, and maintain interactive dashboards (QuickSight, Weave) covering product trends, customer growth, instance utilization, and feature adoption. Today, dashboards serve 100+ Product Managers across 11 engagement areas — you will own dashboards for your service areas and improve self-serve capabilities.
• Stakeholder Partnership: Work closely with Product Managers, service finance teams, and cross-functional partners to translate business questions into data products and present findings to senior leaders. Today, the team partners across EC2, Networking, and Compute product families — you will be the primary analytics point of contact for your assigned service areas.
About the team
We are the EC2 + Networking Product BI team within AWS Analytics & Engineering (AAE). We serve as the data and analytics partner for Amazon Elastic Compute Cloud (EC2), Networking Services, and adjacent Compute product families — supporting 100+ Product Managers across 11 engagement areas.
Our core work includes:
• ETL Pipeline Monitoring & Operations: We build and operate 200+ data pipelines that ingest, transform, and serve petabyte-scale datasets across EC2, Networking, and Compute services. Reliability and timeliness are critical — our reports feed directly into CEO/S-Team weekly reviews. We use automated alarms for real-time pipeline monitoring and AI-powered agents to self-heal failures and triage tasks, minimizing manual intervention at this scale.
• Report Delivery & Callout Generation: We deliver Weekly and Daily Business Review (WBR/DBR) reports across 9 Compute services (EC2 Core, Gen AI, EBS, Bedrock, SageMaker, ECS, EKS, ECR, Lambda), generating callouts on service performance that inform executive decision-making. Report generation, validation, and callout generation are all done via LLMs — enabling consistent quality, accuracy, and speed at scale.
• Data Ingestion & Metric Creation: We design and maintain metrics that track business health — usage, capacity, adoption, customer growth — ensuring they are sustainable, reproducible, and available on demand.
• Analysis & Deep Dives: We produce analyses for Product Managers, Sales, and Finance teams using our proprietary analytics platform where governed SOPs, context, and prior work live. These SOPs help all PMs, Sales, and Finance stakeholders deep-dive with governed data, technical depth, and the right queries — enabling reproducibility and easy follow-ups across the organization.
Everything we build is designed to be sustainable, reproducible, and available on demand — so any team member can pick up, extend, or re-run work without starting from scratch.
Basic Qualifications
- Bachelor's degree in engineering, statistics, computer science, mathematics, or a related quantitative field- 3+ years of experience in business intelligence, data engineering, or analytics engineering
- Proficiency in SQL with experience writing complex queries against large-scale data warehouses (Redshift, Spark, or equivalent)
- Experience with at least one programming language (Python, R, or Java) for data manipulation and analysis
- Experience building and maintaining ETL/ELT data pipelines
- Experience designing and publishing BI dashboards (QuickSight, Tableau, or equivalent)
Preferred Qualifications
- Master's degree in a quantitative field- Experience with AI/ML technologies, including large language models (LLMs) and building automation workflows
- Experience with AWS services (Redshift, S3, Lambda, Glue, SageMaker, Bedrock)
- Experience building self-serve analytics platforms or data products
- Strong data storytelling skills — ability to present complex analyses to senior leadership
- Experience working with Product Management teams in a cloud computing or SaaS environment
- Familiarity with orchestration frameworks (Airflow, Step Functions, or similar workflow engines)
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, Seattle - 99,500.00 - 160,000.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.