Data Modelling Lead

Hirdetés feladója: Career Oppurtinities
Munkavégzés helye: Budapest XIII. kerület (Pest megye)
Jelentkezési határidő: 2022. január 28.
Várható kezdés: 2022. január 31.

We are a global energy business, involved in every aspect of the complex energy system that drives our world.

We operate in more than 70 countries worldwide. We find and produce oil and gas on land and offshore and we move energy around the globe. We manufacture and market fuels and raw materials used in thousands of everyday products, from mobile phones to food packaging.

Elvárások a jelölttel szemben

  • Core systems experience incl. SAP, IBM, Oracle
  • 5 years+ Enterprise Data Modelling experience across all layers is crucial
  • Proficiency in English
  • Strong stakeholder management skills
  • Technology, frameworks & accelerators (ERWIN / Sparks / Zachman / Industry data models)
  • Catalogue & metadata management
  • Data ownership, stewardship & governance
  • Relevant project / change methodology
  • Experience across both operational and analytical settings

 

Szükséges nyelvismeretek

  • Angol - Felsőfok, szóban és írásban

Feladatok

  • Be responsible for modelling-related frameworks, methods and work products and the overall strategic approach to drive value from modelling
  • Establish alignment of technologies to enable record keeping including model management, cataloguing, master, reference and meta data management
  • Define roles and responsibilities including hand-offs and controls for all data modelling SMEs and their relationships with interfacing teams
  • Define and maintain data modelling related work products as part of the DAS data change methodology
  • Represent DAS for all elements of the data model as part of a formal Design Authority providing governance oversight
  • Deliver modelling strategies which are optimized for read & write, curated reusable store as well as responsive analytic constructs
  • Own and maintain the Business Information Model layer of the corporate data model
  • Analyze and group ‘like’ data into business domains
  • Identify new candidate data items to be added to the Business Information Model (BIM), recommend candidate data owners through domain modelling
  • Build physical models which support delivery of analytics-ready data packets for exploitation in a data science setting
  • Design data structures which deliver optimal performance for speed of analytic response
  • Set out mappings to the optimum source of reusable data of known quality
  • Maintain record keeping which determines ‘best version of truth’ and completeness of definitions and quality characteristics
  • Interpret and model inventories of data associated with functions or projects to identify domains and candidate data owners
  • Oversee colleagues and participate in delivery of data modelling activities
  • Educate key partners on the broader role of the data model and how it can be used most optimally across a data change portfolio
  • Engage with IT to avoid a disconnect between a business view of data and the physical view of data structures and application data tables
  • Take accountability for the sign-off of data models produced by projects
  • Input into and approve data warehouse design including the definition of layers, modelling approach for each and their acceptable use
  • Take accountability for resource management of the modelling team

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