Amazon Senior Live Ops Support Engineer Playback Operations Prime Video 

United Kingdom, England, London 

549818850

Then we want to hear from you.
You will have an eye for detail, are proficient in SQL/Python and have a knack for solving challenging data and reporting challenges. The role requires you to feel comfortable working with and clearly communicating with other functional teams, regionally and globally.You would be a great fit for this role if you :• Can use your analytical skills to generate and implement innovative and disruptive ideas
• Can solve complex analytical problems and drawing conclusions from large data sets
• Continuously strive to learn new skills and knowledge areas to grow, develop, and better serve our customers
• Can work with a broad set of stakeholders from diverse and dynamic teamsKey job responsibilities
• Collecting, analyzing and coordinating quantitative data and creating meaningful reports/dashboards to define business improvement and cost reductions
• Root cause analysis and uncovering core issues using data, then assisting the business improve and creating new measures
• Recommending, developing, and implementing policies, processes and programs that guide the organization in maintaining and improving its current position and profitability
• Establishing and maintaining accurate operating and business metrics
• Providing and communicating reporting and analysis to senior stakeholders
• Developing the right performance indicators and maintaining them at scale
• Working with data source providers and technology teams to ensure that key decision data is accurate, automated and timely
• Handling complex priorities and providing level-headed guidance during ambiguous/unexpected events.

- Experience in tax, finance or a related analytical field
- Experience writing complex Excel VBA macros
- Bachelor's degree or equivalent
- Experience defining requirements and using data and metrics to draw business insights
- Experience with SQL or ETL

- Experience working with Tableau
- Experience using very large datasets