Senior Manager Data Analytics

5+ years experience
Strong technical skills are required, including quickly identifying and implementing use cases for automation, data modeling, and deeper analytics using Python and SQL.
Strong analytical skills are required, including the ability to analyze raw data, identify trend drivers, draw conclusions, and summarize actionable recommendations and their forecasted outcomes/implications
Familiarity with Redshift and AWS or strong other experience modeling within and querying from a data lake
Experiencing owning major projects as an end to end individual contributor, from ideation to implementation to communication
Familiarity analyzing data within CRM, OMS, or pricing systems (e.g. Salesforce, Boostr, Hubspot) and sales performance metrics is a big plus
Demonstrated ability to manage large datasets and complex analytical projects
Strong organizational skills, with the ability to aggregate information and data from multiple sources
Experience with Looker or other data visualization/dashboarding tools
Excellent verbal and written communication skills, with ability to convey and package technical findings in layman’s terms

Lead the development of comprehensive revenue analytics, focusing on key performance indicators (KPIs) to track progress against goals and identify revenue growth opportunities.
Own the creation and enhancement of the back-end data infrastructure, extracting and integrating data from a wide variety of sources into Redshift to build automated Looker dashboards to convey data, insights, and trends
Understand different categories of data and their locations
Communicate concise data points, trends and measurement strategies to a broad audience of both technical and non-technical teams
Collaborate with other non-technical teams within the business (such as finance, ad operations and sales) to develop reporting and assist in ad hoc requests
Build robust data visualizations and interactive dashboards that are capable of delivering information in an intelligent and digestible manner
Partner with Data Science and Data Engineering teams to deliver data solutions which meet business and technical requirements
Peel through layers of reported data, to deliver analysis and insight to both internal and external client constituents
Adapt and move quickly in a fast paced environment, with a pragmatic approach to analysis
Mentor junior analysts and manage their professional development

Familiarity analyzing data within CRM, OMS, or pricing systems (e.g. Salesforce, Boostr, Hubspot) and sales performance metrics is a big plus