Business Intelligence Engineer

Job description

DESCRIPTION

An opportunity has arisen for a Business Intelligence Engineer to join Amazon's worldwide Dynamic Advertising program based in Edinburgh, Scotland.

Our Dynamic Advertising program serves relevant personalized ads to our customers across the internet. We apply machine learning to bid optimally for advertising impressions in real-time auctions and serve the most relevant ads to customers in every impression. Our work is characterized by high scale, low latency, complexity and a constant need for innovation.

The right candidate will have data analysis expertise as well as experience setting up reporting tools, querying and managing data warehouses. You will 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 advertising strategies worldwide.
· Setup and maintain BI tool, reports and dashboards.
· Support the business with time-critical tactical data analyses.
· Collaborate with business stakeholders to improve the team's 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, Redshift, Tableau 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.
· Experience data modeling and transformation of large scale data sources using SQL, Hadoop, Spark, Hive, EMR, or other Big Data technologies.
· Demonstrated development and application of predictive statistical procedures in languages such as R, SAS, SPS.
· Bachelors or Masters degree in Business, Engineering, Statistics, Computer Science, Mathematics or a 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.