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DATA MODELLING LEAD - CONTRACT - REMOTE (UK/EU) - UTILITIES/ENERGY EXPERIENCE REQUIRED
We're supporting a consultancy partner that is delivering an important piece of work for a major Energy/Utilities business.
Role Overview
The Data and Analytics Office (DAO) where this role resides is a key function of the broader Digital and AI division tasked with creating and executing a compelling vision for factual decision making to enable the delivery of the ambitious version.
Role Purpose
Accountability and ownership for the development, maintenance and continuous improvement data models,, including the Enterprise Data Model (EDM) and Information Map (IM).
KEY ACCOUNTABILITIES & ACTIVITIES
·Lead data modelling efforts across digital projects for applications i.e. CRM, GIS, Asset Management, Digital Twin etc. and across analytics projects.
·Review, collate and integrate data models of new internal and external platforms and systems to ensure one overall integrated whole.
·Lead in the establishment, development and maintenance of the Enterprise Data Model (EDM), Information Map (IM), Business Glossary and overall data ontologies and taxonomies.
·Own, review, organize and oversee implementation of various industry data standards and how they are to be leveraged/integrated with the EDM e.g. CFIHOS, CIM, Utility Reference Data Models, IAE, IEE standards.
·Lead in the alignment and education of how stakeholders define, understand and think about data, bringing everyone on a journey of consistency, standardization and agreed meaning.
·Lead in gaining widespread agreement of data entities and terms at contextual and conceptual levels, recognising that collaboration with broad and agreed meaning of key terms is more important than accurate detailed representation of many terms, aligning a practical approach to the maturity of the organisation.
·Lead in the structured analysis of business data requirements, translating these into conceptual and logical data models representing business concepts and functional requirements in collaboration with business analysts, subject matter experts and product owners.
·Oversee, maintain and lead in the development of physical data models.
·Lead in the implementation and integration of a data modelling tool and how it integrates with other architecture tools (Mavem) and metadata (Alation) tools.
·Ensure appropriate classification of data working closely with data privacy, protection and security teams.
·Facilitate and promote the re-use of data by providing users access to data model repositories and assisting users as to how it is organized and how it can be used.
·Chair and direct the Data Modelling Working Group to align different domains in the data model journey.
·Define processes for how and where the EDM should be used, consulted or when it should direct data and application solutions in both BAU and change.
·Build data modelling capabilities including but not limited to standards, versioning, review, assurance, templates, artefacts etc.
BACKGROUND, SKILLS & QUALIFICATIONS
Knowledge, Skills and Experience
·Minimum 10+ years conceptual, logical and physical modelling
·Different data modelling approaches e.g. relational, dimensional
·Water, utilities and/or energy sector, with deep understanding of the Common Information Model (CIM) or other Utilities related models and standards.
·Data modelling for transactional applications
·Data warehouse, data lake, and enterprise big data platforms
·Physical data storage e.g. relational DBs, NoSQL, big data, columnar.
·Data Architecture and Data Governance tools e.g. Erwin, Alation etc.
·Agile and how this applies to modelling e.g. BEAM, ADM, SAFe
Knowledge
·Strong knowledge of and across all data capabilities and processes
·Practical knowledge of industry frameworks and their use e.g. DAMA DMBoK, CMMI DMM, TOGAF.
·Business process modelling and its relationship to data modelling
·Good understanding of graph databases and their use cases
·Good understanding of semantic ontologies
Interviews happening Thursday 15th and Friday 16th August. September 1st start date.