Business Intelligence Engineer

Job description

DESCRIPTION

The Social Ads team owns Amazon's automated advertising on Social Media platforms like Facebook, Twitter, Pinterest and Instagram. Our engineering team builds self-optimizing ad personalization engines that leverage integrated Machine Learning, massive data processing and adaptive algorithms to deliver ad performance. We use Social Graph signals and closed loop optimization to power our advertising engine. As a part of our team, you will have a chance to have a ground-up impact on our systems, our business and most importantly, our customers, through the leadership of a team of technologists focused on scaling Social advertising.

The right candidate will have data analysis expertise as well as experience setting up reporting tools, querying, managing data warehouses, be hands-on with big data and use statistical concepts to design experiments.

Key responsibilities:
· Produce written recommendations and insights for key stakeholders that will help shape effective marketing strategies worldwide.
· Setup and maintain BI tool, reports and dashboards.
· Support business with time-critical tactical data analyses.
· Collaborate with business stakeholders to improve the teams reporting toolset and insights.
· Create the performance sections of weekly, monthly and quarterly business review documents.
· Shape and inform key metrics and indicators by which the organization will assess its performance.
· Design and execute experiments, and assist in statistical significance and power analysis.
· Learn and understand a broad range of Amazon's data resources and know how, when and which data sources to use
· Deep dive into massive data sets to answer key business questions using MS Excel, Oracle SQL and other data manipulation languages

Desired profile

BASIC QUALIFICATIONS

· Relevant experience in data analysis, research, business intelligence and data warehousing tools, or comparable consumer analytics solutions
· Advanced skills using SQL, ETL and databases in a business environment with large-scale, complex datasets
· Bachelors or Masters degree in Business, Engineering, Statistics, Computer Science, Mathematics or related field.
· Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause analyses.