Mondelz International, Inc. empowers people to snack right in over 160 countries around the world. We- re leading the future of snacking with iconic brands such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. Our 90,000+ colleagues around the world are key to the success of our business. Great people and great brands. That's who we are. Join us on our mission to continue leading the future of snacking around the world by offering the right snack, for the right moment, made the right way. Purpose of Role This role will be required to develop integration data models between multiple disparate data sources and consolidate them into a single common data model, or enterprise data model. Unlike many enterprise data models, this one will actually be used as a key component of the Next Generation Big Data Platform. On a day-to-day basis, the successful candidate will be proficient in data modeling techniques, and well as capable of discussing and communicating business rules, and how to implement those rules in a data model. This is not a large data modeling team, so the candidate will be responsible for maintaining version control of the data model(s), as well as ensuring consistency between the data model and deployed instances of the model. the candidate will be responsible for maintaining version control of the data model(s), as well as ensuring consistency between the data model and deployed instances of the model. Collaborative, good communication skills, a strong work ethic, and a willingness to pitch in and get the job done are essential characteristics for the successful candidate.The candidate will be responsible for maintaining version control of the data model(s), as well as ensuring consistency between the data model and deployed instances of the model. Collaborative, good communication skills, a strong work ethic, and a willingness to pitch in and get the job done are essential characteristics for the successful candidate. Main Responsibilities - Knowledgeable of all data model types and terminology including OLTP/OLAP, Normal Forms, dimensional, star, snowflake, cube, and graph/NOSQL. - Be able to speak to the differences in data modeling techniques and philosophies of Codd, Kimball, and Inman. - Understand and clearly define differences between entities, tables, attributes, and columns. - Capable of building conceptual, logical, and physical data models in Erwin and/or ER Studio complete Have mastery of tools such as Hadoop, BI sufficient to perform data profiling - expert level in SQL Understand and apply data naming standards, and explain your definition of "best practices in data modeling" - Data profiling, assessment, and defining data changes needed to make the data the target level of business usefulness Data mapping from source to target data models . Design and Development of needed Data Architecture for their area of domain and ensures enterprise data is structured for ease of use - Governs the Data Flow &amp; 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 a process for capturing and maintaining metadata from all data market place components - Level 3 support of all processes and solutions within a domain - Defines Archiving and housekeeping approach and ensures consistent use - Strong relational and dimensional Data modeling and information classification expertise - Understanding of the differences between relational and object modeling - Understanding of meta-models, taxonomies and ontology- s, as well as the challenges of applying structured techniques (data modeling) to less-structured sources - Familiarity with MDM, business intelligence, and data warehouse development techniques with SAP BW, SAP HANA, Hadoop - Deep understanding of data within their domain (master data, data facts, KPI's, etc.)and related business challenges - Drive for Results - Problem Solving Planning - Creativity - Listening - Perseverance - Informing - Peer Relationships - Integrity and Trust - Business Acumen - Decision Quality" Career Experiences Required &amp; Role Implications - 8-10 years of experience in Big data space - Hadoop and similar Big data technologies along with at least one domain experience

Mumbai

Mondelez - Data Modeler  

Mondelez - Data Modeler   ,Job Description for Mondelez - Data Modeler   in Mondelez in  Mumbai for (8-10) years of experience. Apply Now!

Job Description for Mondelez - Data Modeler   in Mondelez in  Mumbai for (8-10) years of experience. Apply Now!