At Amazon we are striving to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright and curious people. We are looking for a Sr. Business Intelligence Engineer to lead in delivering scalable data engineering and analytics solutions as part of the EU Marketplace Business Intelligence team. This role provides a unique opportunity to explore petabytes of data in one of the world's largest data lakes, employing cutting-edge tools and techniques. Your mission will be to deep-dive in these sources of information, reveal insights and construct sustainable Analytics artifacts to drive the growth of Amazon Stores in Europe.
Key job responsibilities
- Support leadership decision-making by deep-diving into business hypotheses and anecdotes.
- Design and automate ETL pipelines for business metrics.
- Design insightful dashboards for a senior non-tech audience.
- Research the most appropriate methodologies for a given analytical problem.
- Contribute to key business documents.
- Collaborate with business stakeholders and tech teams across functions and geographies.
We are open to hiring candidates to work out of one of the following locations:
Milan, MI, ITA
BASIC QUALIFICATIONS
- Quantitative or engineering background (e.g. degree in Computer Science, Mathematics, Economics, Physics, etc.).
- 5+ years relevant experience.
- Highly proficient in SQL.
- Experience in ETL processes with large datasets.
- Experience with one or more scripting languages (e.g. Python, R, Matlab, SAS).
- Experience with one or more industry analytics and metrics visualization tools (e.g. Excel, QuickSight, Tableau, MicroStrategy, PowerBI).
- Proficient in descriptive statistics and familiar with inferential statistics and experiments design.
- Experience working directly with business stakeholders to translate between data and business needs.
- Excellent verbal and written communication skills.
PREFERRED QUALIFICATIONS
- Master's degree in a quantitative or engineering field.
- Experience with AWS technologies for data analytics (e.g. Redshift, S3, SageMaker).
- Experience with theory and practice of data science, machine learning and data mining.
- Clear communication with senior stakeholders and leadership.