BI Engineer II: Network Design Analytics

Amazon

Bellevue (WA)

On-site

USD 100,000 - 160,000

Full time

26 hours ago

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Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Business Intelligence Engineer II to design and build scalable data solutions powering performance insights and informed decisions across teams. You will own end-to-end analytics from data modeling to visualization, tackling ambiguous problems with rigor and delivering high-quality data products that influence strategy at scale.

You will collaborate with engineers, scientists, and product teams to transform vague requirements into measurable deliverables and improve data

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 processing large, multi-dimensional datasets from multiple sources experience
1+ years of performing statistical analysis experience
1+ years of developing automated reporting experience
3+ years of in the job offered or a related occupation experience
1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle 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
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Responsibilities

Run and Improve Network Design Models working with Technical Product Managers and Applied Scientists and analyze the modeled outputs
Design, build, and maintain mid-to-large-scale BI solutions including data models, ETL pipelines, and curated datasets that serve as trusted sources of truth for business reporting and decision-making.
Develop intuitive dashboards, reports, and visualizations using industry analytics tools to surface key metrics and enable stakeholders to self-serve insights where appropriate.
Collaborate with cross-functional partners — including data engineers, data scientists, product managers, and business teams — to refine ambiguous problem statements into specific, measurable deliverables that address real business needs.
Apply statistical methods and analytical techniques to complex business questions, clearly communicating findings, assumptions, and limitations to both technical and non-technical audiences.
Improve data quality and operational excellence by documenting data lineage, maintaining clear design documentation, and mentoring peers on how your team's BI solutions are constructed and consumed.