Global Data Solutions Delivery Analyst

12 ago - Sesto San Giovanni
Altro

Campari Group today is a major player in the global branded spirits industry, with a portfolio of over 50 premium and super premium brands, marketed and distributed in over 190 markets around the world, with leading positions in Europe and the Americas.
Headquartered in Milan, Italy, Campari Group owns 25 plants worldwide and has its own distribution network in 26 countries, and employs approximately 4,700 people.
Shares of the parent company Davide Campari - Milano N.V. are listed on the Italian Stock Exchange since 2001. Campari Group is today the sixth-largest player worldwide in the premium spirits industry.
General Description Of The Role In the Technology & Services organization, the Data & Analytics Team enables data-driven decisions by turning data into reliable insights that support business strategy and performance.
The team works with business and technical stakeholders to manage the data lifecycle, deliver analytics solutions, strengthen data governance and literacy, and define value-driven data strategies and use cases.




The team partners with business and technical stakeholders to manage the data lifecycle, deliver analytical solutions, promote data governance and literacy, and support the definition of data strategies and use cases aligned with business priorities.
Within the Data & Analytics team, the Data Solutions Delivery Analyst – Sales & Marketing supports the delivery and evolution of Sales & Marketing data products, reporting solutions and data integrations. The role helps translate business needs into clear requirements, supports delivery activities, monitors data product performance and collaborates with business, technical teams and external partners.
Key Responsibilities And Activities Data Platform, Modelling and Architecture Support Support data integration scope definition and documentation for Sales & Marketing sources such as Nielsen, CRMs, external marketing agencies and commercial enterprise systems
Contribute to data modelling by do

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