Business Analytics & Intelligence Manager

The Walt Disney Company•Glendale, CA

6d•$115,500 - $154,800•Onsite

About The Position

Do you love using data to answer complex questions? Then you may be interested in learning more about the Licensing Analytics team at Disney Consumer Products! Our mission is to put our data assets to work and apply quantitative techniques to discover previously unknown insights about our licensing partners, retailers and consumers. We work directly with the major decision-makers who shape the Disney Consumer Products experience. Through our insights, we help form and improve Disney offerings. This role sits onsite in Glendale, CA and reports to the Director, Licensing Analytics.

Requirements

5+ years of experience in analytical roles
Experience leading the lifecycle of analytic products; from requirements gathering to data acquisition to presentation of results, and automation (where applicable)
Proficient project management skills; ability to organize and manage projects of varying complexity and length
Takes initiative and is a self-starter, with the ability to lead projects from inception to completion
Advanced user of Tableau, Power BI, and/or other data visualization software
Time-management skills, with ability to prioritize multiple requests and communicate status to partners
Strong written and verbal communication skills, with the ability to communicate complex ideas and develop concise recommendations
Comfort in working in ambiguity to determine the questions that should be answered and the approach and partners needed to get there
Experience with working and curating structured and unstructured data
Technical proficiency in these data technology subject areas: Data pipeline technologies and ETL tools and languages such as SQL, SSIS, Knime, Alteryx, Tableau Prep; Database technologies such as Snowflake, SQL Server; Data Visualization and Consumption Tools — primary proficiency in Tableau required; familiarity with Microstrategy, Power BI, or Business Objects a plus; Data warehouse and data lake architecture

Nice To Haves

External syndicated data platforms such as Circana, Euromonitor, and Statista — ability to extract, interpret, and activate third-party market and category data is strongly preferred
Scripting languages such as Snowscript, Javascript, VBA, Python - Preferred
Experience working with large scale retail systems data
Experience working with cloud platforms/technologies
Experience with machine learning

Responsibilities

Support the Retail & Marketing teams, serving as the primary analytics lead for developing and facilitating analysis linked to owned retail and licensee data enhanced through industry & macro insights.
Facilitate analyses and projects across cross-functional teams with direct and indirect leadership of analytics and data partners.
Support evaluation of product performance, consumer & macro-economic trends, and industry shifts to inform strategic insights.
Help drive the technical transformation of our team by executing against and evolving a technology roadmap (focused on automating & structuring data loads and mapping), deploying self-service reports, defining a data architecture & governance strategy, and optimizing processes against business needs.
Identify appropriate external data sources, reconciling data sets, identifying proxies, and clearly communicating the assumptions behind the analysis.
Use knowledge of visualization techniques to create compelling dashboards and intelligence tools to enable ease of interpretation of commercial performance metrics.
Code the backend processes to quickly access needed data and develop decks that synthesizes complex data into a compelling story.
Translate the business and analytical needs into data requirements to support timely data delivery, routine reporting, and in-depth analysis.
Work in large and complex data environments to compile and curate data from a variety of domains and sources to build a foundation for DCP Licensing Analytics.
Develop fully automated data pipelines and analytical tools to minimize time spent on data gathering and preparation.
Collaborate closely with Technology partners to enhance data quality and governance.
Leverage data analytics and visualization skills to conduct in-depth analysis with enhanced data streams and quality.
Build & maintain the data foundation that enables self-service analytics, AI-driven insights, and scalable reporting.
Stay up to date with industry trend on robotic automation & AI / ML to identify areas for process improvements.
Develop easy-to-use tools and share best practices with peers to solve problem efficiently and effectively.
Translate technical terms into easy-to-understand outputs.
Partner with IT to systemize planning process leveraging data from disparate sources.
Be willing to be flexible with changing business needs and adaptable with work requests.