Sr. Business Intelligence Engineer, AWS Analytics Engineering

Socket.dev

Seattle (WA)

On-site

USD 130,000 - 176,000

Full time

7 days ago
Be an early applicant
Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Benefits offered by this job

Health insurance (medical, dental, etc
401(k) matching
Paid time off
Parental leave

Job summary

Amazon is seeking a Sr. Business Intelligence Engineer to own the end-to-end analytical roadmap for Amazon Quick. You will partner with product, business, finance, and engineering leaders to translate complex business questions into data-driven insights and scalable analytics.

You will help shape AI-enabled analytics capabilities and drive adoption and growth. You will work in one of the world’s largest data warehousing environments, delivering insights that influence product decisions and

Qualifications

  • 5+ years of SQL experience.
  • Experience programming to extract, transform and clean large data sets.
  • Experience with data modeling, warehousing and building ETL pipelines.
  • Experience with AWS technologies.
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.

Responsibilities

  • Own and deliver the end-to-end analytical roadmap for Amazon Quick.
  • Generate data-driven insights to drive adoption, engagement, and growth at leadership level.
  • Build scalable data pipelines and models to derive key metrics from large datasets.
  • Collaborate with product, business, finance, and engineering leaders to translate complex problems into outputs.
  • Develop agentic capabilities to automate and accelerate analytical work.

Skills

SQL
ETL pipelines
Data modeling
AWS technologies
Python

Tools

QuickSight
Tableau

Job description

AWS is looking for a Sr. Business Intelligence Engineer to join the AWS Analytics Engineering (AAE) team supporting Amazon Quick. Formerly Amazon QuickSight, Quick has evolved from a standalone BI service into a comprehensive, generative-AI-powered business intelligence platform that combines traditional analytics with modern AI assistance. It brings together two complementary experiences. Amazon Quick Sight is the cloud-native dashboarding and visualization engine that powers governed datasets, interactive dashboards, and ML-driven insights such as forecasting and anomaly detection. Alongside it, an agentic AI layer lets users chat with their data, conduct deep research, and automate multi-step workflows across connected enterprise sources through natural language. Available in the browser, as a desktop companion, and through extensions for Slack and Microsoft Office, Quick is used to turn data into decisions and actions, without requiring machine learning expertise. This is your opportunity to shape the analytical foundation of one of AWS's fastest-evolving products.

As a Sr. BIE on this team, you will own the end-to-end analytical roadmap for Amazon Quick. You will generate insights that directly drive adoption, engagement, and growth, and that influence product and feature decisions at the leadership level. You will work with datasets in one of the world's largest data warehousing environments, developing and supporting your hypotheses with data-driven analysis. You will partner closely with product, business, finance, and engineering leaders to tackle non-standard, ambiguous business problems and translate them into actionable output. You will be part of a business intelligence team that goes beyond reporting and drills into the drivers behind key business metrics, redefining best practices with a cloud-based approach to scalability and automation.

Beyond building analytics for Amazon Quick, this team is reimagining how analytical work itself gets done. We are developing agentic capabilities that automate and accelerate the daily workstream of a business intelligence engineer, from building reports to answering analytical questions on demand. As a Sr. BIE, you will help shape and adopt these capabilities, both applying them to scale your own impact and informing how they evolve. This is a rare opportunity to practice business intelligence on a platform you are helping to build, and to redefine analytical best practices for an AI-native era.

Key job responsibilities
  • Develop a deep understanding of the business drivers, customer behavior, and data landscape for Amazon Quick.
  • Own and deliver a comprehensive reporting and analytical roadmap that surfaces the key metrics for adoption, engagement, and growth.
  • Deliver in-depth, data-driven analysis papers with actionable insights for business and product leaders.
  • Design and build scalable data pipelines and models to derive key business metrics from large, complex datasets.
  • Collaborate with cross-functional teams to identify and onboard new data sources that expand analytical coverage.
  • Communicate findings clearly to business, finance, product, and technical audiences to influence decision-making and product enhancements.
  • Build and adopt agentic capabilities that automate and accelerate analytical work, from report generation to answering analytical questions on demand.
  • Mentor junior engineers and help establish new analytical standards and best practices for the team.
About the team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

Basic Qualifications
  • 5+ years of SQL experience
  • Experience programming to extract, transform and clean large (multi-TB) data sets
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with AWS technologies
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
Preferred Qualifications
  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience managing, analyzing and communicating results to senior leadership
  • Experience with data visualization using QuickSight, Tableau, or similar tools

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.

  • 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

Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually

Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Sr. Business Intelligence Engineer, AWS Analytics Engineering
Sr. Business Intelligence Engineer, AWS Analytics Engineering

Amazon Web Services (AWS) • Seattle (WA)

On-site
USD 130,000 - 176,000
Health insurance
401(k) matching
Paid time off
+2
Sr. Business Intelligence Engineer, AWS Analytics Engineering
Sr. Business Intelligence Engineer, AWS Analytics Engineering

Amazon • Seattle (WA)

On-site
USD 130,000 - 176,000
Sr. Software Development Engineer, Amazon Quick
Sr. Software Development Engineer, Amazon Quick

Socket.dev • Seattle (WA)

On-site
USD 168,000 - 228,000
Health insurance
RSUs
401(k) matching
Sr. Software Development Engineer, Amazon Quick (AWS)
Sr. Software Development Engineer, Amazon Quick (AWS)

Amazon • Seattle (WA)

On-site
USD 168,000 - 227,000
Health insurance
401(k) matching
Paid time off
+3
Senior Product Manager - Technical, Quick Sight - Structured Data Analytics
Senior Product Manager - Technical, Quick Sight - Structured Data Analytics

Amazon Web Services (AWS) • Seattle (WA)

On-site
USD 151,000 - 205,000
RSUs
Health insurance
401(k) matching
+1
Business Intelligence Engineer II, Alexa Devices Business Insights
Business Intelligence Engineer II, Alexa Devices Business Insights

Amazon • Seattle (WA)

On-site
USD 100,000 - 160,000
Health insurance
RSUs / stock options
Business Intelligence Engineer II, Alexa Devices Business Insights
Business Intelligence Engineer II, Alexa Devices Business Insights

Amazon • Bellevue (WA)

On-site
USD 100,000 - 160,000
Health insurance
RSUs
401(k) matching
+1
Senior Business Intelligence Engineer, Infra Supply Chain Automation
Senior Business Intelligence Engineer, Infra Supply Chain Automation

Amazon Web Services (AWS) • Seattle (WA)

On-site
USD 130,000 - 176,000
Health insurance
401(k) matching
Paid time off
+1
BIE, Applied AI Solutions
BIE, Applied AI Solutions

Amazon • Seattle (WA)

On-site
USD 100,000 - 160,000
Health insurance
401(k) matching
Paid time off
+1
Senior Software Development Engineer, Amazon Quick (AWS)
Senior Software Development Engineer, Amazon Quick (AWS)

Amazon • Seattle (WA)

On-site
USD 168,000 - 227,000
RSUs
Health insurance
401(k) matching
+1