Talent Acquisition Specialist at Mondelez
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Mondelez - Business Intelligence Data Modeler - Marketing Domain (9-13 yrs)
Broad function and scope of the position:
- Depicts the data flow within and between systems in a particular functional area.
- Works with key business representatives to model the data needed for the respective domain.
- Develops, manages and updates the data models, including physical and logical models of the data warehouse, data mart and staging area and sometimes the operational data store and data source systems
- Design and Development of needed Data Architecture for Marketing domain and ensures enterprise data is structured for ease of use
- Governs the Data Flow & Model and Layering concept for their domain and ensure consistent and harmonized application
- Develops and maintains an integrated, subject-oriented, predominantly conceptual and logical data model that represents essential data produced and consumed across the enterprise for a domain
- Provides data architecture support and expertise to all major enterprise projects
- Develops process for capturing and maintaining metadata from all data market place components
- Ensures safeguarding the data model consistency, the data flows process structure and the data integrity
- Level 3 support of all processes and solutions within a domain
- Defines Archiving and housekeeping approach and ensures consistent use
Experience and Skills Required:
- Deep understanding of Marketing and related processes in CPG or FMCG and industry
- Deep understanding of data within their domain (master data, data facts, KPI's, etc.) including Markets, Consumers, Brand, Categories, Products, Channels, Volume/Value, Market Share, promotion, modern trade, E-Commerce, etc. and related business challenges
- Strong relational and dimensional Data modeling and information classification hands-on expertise
- Understanding of the differences between relational and object modeling
- Deep knowledge and hands-on experience with Multi-dimensional modeling, star and snowflake schemas and normalization/ /de-normalization
- Deep experience with Hadoop and Non-SAP based data modeling
- Hands-on experience in Data Harmonization, Slowly Changing Dimensions - Type I & II, etc.
- Understanding of meta-models, taxonomies and ontology- s, as well as the challenges of applying structured techniques (data modeling) to less-structured sources
- Experienced with Data Architecture for structured, semi-structured and unstructured data
- Exposure to Hadoop technologies like Hive, HBase, Oozie, Pig, Sqoop, Spark
- Awareness of ELT processes through hadoop
- Development of user defined functions (udf) using java, python, shell scripts (Good to Have)
- Experience of modeling using high volume data from 3rd party Data providers (like Nielsen, Kantar, Ipsos, etc.) and from SAP
- Familiarity with MDM, business intelligence, and data warehouse
- Deep knowledge in designing & developing data flows and enabling process chains on Hadoop based technologies
- Good understanding of views, Synonyms, Indexes, Joins and Partitioning
- Drive for Results
- Problem Solving Planning
- Creativity
- Listening
- Perseverance
- Informing
- Peer Relationships
- Integrity and Trust
- Business Acumen
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