Manager, Data Analytics

The Hershey Company-posted 4 months ago

Full-time • Manager

Remote • Hershey, PA

Food Manufacturing

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The Manager, Data Analytics (Semantic Layer) is responsible for overseeing the data analysis and reporting processes - including Semantic Layer development and implementation. This role involves developing and implementing data strategies, end-to-end data products, knowledge graph semantic layering, ensuring data integrity, and leveraging data insights to drive business decisions. The manager will collaborate with various teams to optimize data systems, support enterprise architecture initiatives, and ensure compliance with data governance policies.

Lead, Develop and Implement Data Strategies: Create and execute data analysis, data collection systems, and other strategies to optimize statistical efficiency and quality.
Lead, Develop and Implement Semantic Layer Knowledge Graphs: Support data platforms throughout a data product lifecycle with data organization by data product and data domains, including standardized KPIs, centralized definitions, and governance compliance.
Data Management and Integrity: Ensure the accuracy, consistency, and security of data across the organization by maintaining databases and data systems.
Trend Analysis and Reporting: Identify, analyze, and interpret trends or patterns in complex data sets and prepare accurate reports for upper management.
Collaboration and Coordination: Work with different functional teams to implement data models, monitor outcomes, and support enterprise architecture projects.
Compliance and Governance: Ensure adherence to data management and governance regulations and policies, maintaining a robust risk posture for data assets.
Data Strategy Documentation: Comprehensive documentation of data strategies, including data collection methods, analysis techniques, semantic layer knowledge graphs, and data governance policies.
Semantic Layer design, development, and adoption across the Enterprise - driving adoption rates, time-to-insight, and consistent data solutions.
Trend Analysis Reports: Regular reports highlighting key trends, patterns, and insights derived from data analysis to inform business decisions.
Data Integrity Audits: Periodic audits to ensure data accuracy, consistency, and security, along with recommendations for improvements.

Technical Proficiency: Strong knowledge of data analysis tools and techniques, including proficiency in SQL, Python, and data visualization tools.
Data Platform Proficiency: Strong knowledge and experience in working directly with a Data Platform team, supporting Data Product lifecycles, and enabling Semantic Model Knowledge Graphs.
Analytical and Critical Thinking: Ability to analyze complex data, identify patterns, and make data-driven decisions.
Communication and Collaboration: Excellent communication skills to present data insights clearly and collaborate with cross-functional teams.

A Master's degree in Business Administration, Data Science, or a related field is preferred.
Experience in enterprise architecture and data governance is highly desirable.

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