Are you excited about building data pipelines and analytics tools that power strategic capital investment decisions at Amazon scale? The WWEI MHE & Automation PMO team is looking for a Business Intelligence Engineer to be the founding analytics hire for a new program management function supporting Amazon's global last-mile delivery station automation portfolio - a $1B+ annual capital program spanning 150+ sites across NA and EU.
You will design and build automated dashboards, data models, and ETL pipelines that replace fragmented Excel-based reporting with self-service QuickSight analytics. Your work directly enables three PMO workstreams: capital project portfolio tracking, site launch intelligence, and workforce/resource planning. You'll integrate data from internal platforms (enterprise data lakes, project management systems, procurement platforms, and approval workflows) into unified views that leadership uses daily to make multi-million dollar investment decisions.
Key job responsibilities
- Design and build ETL pipelines connecting internal data sources (enterprise data lakes, project tracking systems, procurement platforms, and approval workflows) into a unified analytics layer using Redshift and S3
- Develop and maintain Amazon QuickSight dashboards for capital project tracking (inventory, funding status, closure timelines), site launch status, and resource utilization
- Lead migration of manual Excel consolidation (9+ regional spreadsheets) into automated, self-refreshing data models
- Partner with three PMO program managers to translate business requirements into scalable BI solutions - from requirements gathering through production deployment and iteration
- Build data quality monitoring frameworks ensuring dashboards reflect ground truth within defined SLAs
- Leverage existing internal data platforms and curated data layers rather than building bespoke ingestion from raw sources
- Support operational reporting cadences: Monthly Business Reviews, Flash Reports, Prime event daily trackers, and ad-hoc VP-level requests
- Design the data architecture for a resource utilization model (people-per-task calculations derived from project hours, roster data, and historical actuals)
A day in the life
You start the morning reviewing pipeline health - ensuring overnight data refreshes landed correctly for the capital project dashboard and site tracker. A program manager pings you: the EU spend-vs-plan view shows a $2M discrepancy, so you trace it to a schema change in the procurement feed and push a fix. After standup, you spend focused time building the resource utilization data model - pulling roster data, project hours, and historical actuals to calculate how many field engineers each automation type requires at steady state. In the afternoon, you pair with a partner data engineering team to onboard a new project milestone feed, then walk a VP through a prototype dashboard and incorporate their feedback. Your work removes hours of manual Excel consolidation per week and gives leaders answers in seconds instead of days.
About the team
The WWEI MHE & Automation PMO is a newly formed function within Amazon's World Wide Engineering and Innovation organization. We manage the capital portfolio, resource planning, and operational reporting for Amazon's delivery station automation programs - including automated sortation (ADTA), robotic induction, Tetromino next-generation building templates, and 15+ other technology deployments across 6 continents. Our team is building the PMO discipline from the ground up, which means you'll have outsized influence on tooling choices, data architecture, and team standards. We value automation over manual effort, building on existing platforms rather than reinventing, and making data accessible to non-technical stakeholders who need answers fast.
BASIC QUALIFICATIONS
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 1+ years of SQL, ETL or Oracle experience
- 1+ years of developing automated reporting experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
PREFERRED QUALIFICATIONS
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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, TX, Austin - 99,500.00 - 160,000.00 USD annually
USA, WA, Bellevue - 99,500.00 - 160,000.00 USD annually
