Ice Cream Customer Analytics Engineering Lead
Listed on 2026-02-16
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IT/Tech
Data Analyst, Data Engineer
Scope
US, Customer Development
LocationEnglewood Cliffs, NJ - Hybrid (Minimum 2 Days in Office)
Terms & ConditionsFull time, International sponsorship or relocation not supported
About Ice CreamTMICC Ice Cream is the largest global Ice Cream Company in the world, with over 100 years of experience delivering a diverse range of indulgent, yet responsible, craft food experiences and treats delighting consumers. We have 35 brands, including Magnum, Wall’s and Ben & Jerry’s, with a strong presence in over 60 countries and annual revenue of over $8 billion. We operate in a highly attractive category within the broader snacking and refreshment industry.
We are investing to unlock the full growth potential of Ice Cream as a standalone entity, once we separate from Unilever, planned by the end of 2025. We emphasize talent development and career growth within the new organization.
Life Tastes Better with Ice Cream. We craft the future through innovation and imaginative minds, creating unique products and joyful experiences. We are serious about happiness and aspire to create the coolest products with warm hearts.
Job PurposeThe Customer Analytics Engineering Lead will report to the Associate Director of CD Analytics and Insights and will be responsible for the next generation of data capabilities and the data foundation, ensuring the US Customer Development function has the data, analytics, and tools necessary to achieve its sales ambitions. This role involves building and architecting a scalable data analytics platform and leading a team to advance Magnum’s selling capabilities across sales, category management, shopper marketing, and channel strategy.
It is a hands-on technical role with strong business integration, working with commercial and customer development stakeholders to co-design data solutions that integrate into business processes.
- Work closely with business stakeholders to translate needs into well designed technology products embedded into daily decision-making, focusing on promotion optimization, syndicated and retailer data, demand forecasting, shopper marketing, digital commerce, and sales reporting
- Design & implement a modern data lake environment to support scalable ingestion, transformation, and storage of retailer, syndicated, and internal data
- Establish the semantic layer and data modeling framework, defining consistent business logic and unified data definitions to enable self-service analytics and integration across data products
- Build and operationalize advanced analytic models, including demand forecasting, promotion performance, assortment optimization, and shopper behavior modeling
- Collaborate with local and global business and technology teams to define, manage, and enhance Magnum’s Customer Development analytics capabilities
- Maintain awareness of market offerings from third-party data and tools
- Support the Customer Development Leadership Team (CDLT) in achieving key sales KPIs
- Technical aptitude and the ability to lead teams toward business-value focused technology solutions
- 8+ years of experience with cloud data platforms (Azure, AWS, GCP) and Databricks, with strong proficiency in SQL, PySpark, Python, and DAX
- Hands-on experience with Databricks, Azure Data Factory, Delta Lake, Power BI, DBT, Alteryx and related cloud data technologies
- Experience with data visualization tools like Power BI, Tableau
- Strong ability to communicate technical findings to non-technical audiences
- Intellectual curiosity and strong analytical ability
- Willingness to develop a deep understanding of business operations and needs for the Customer Development function
- Excellent planning, organization, and project estimation skills
- Strong understanding of retailer and syndicated data usage and management
- Ability to work collaboratively with cross-functional teams locally and globally
- Ability to clearly and compellingly present complex topics to business stakeholders
- Strong understanding of data engineering principles and approaches
- Solid understanding of data modelling and semantic layer design to support analytics and reporting
- Proficiency in Python, PySpark, DAX and SQL
- Ab…
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