Job Description
Role Responsibility
- Develop conceptual and logical data model including and entity relationship model for the Enterprise based on core data domains of an investment manager (instrument, index, position, transaction, account, product etc) representing entity relationships to underpin the technical build for consistent data structures
- Develop secondary level of detailed model for key enterprise domains, feeding into strategy definitions for those domains and target state design
- Develop a framework of data principles, patterns, and standards for data management, integration, and consumption
- Document a standard mapping for data flow from source through the data lake/lakehouse through to consumption to drive consistency in mapping documentation across projects and domains
- Support and lead as appropriate discussions with Technology to explain the LDM and confirm how this will be delivered through technical development
- Liaise with SMEs within Data Group, Technology and Transformation and Change as required to understand data coverage in existing and legacy solutions to inform the data architecture blueprint
- Socialise data model and architecture with Data Group and work to understand impact / changes to existing data capabilities and approaches e.g. data cataloguing, metadata management, taxonomies, data quality management
- Document approach to implementing logical data model for the enterprise, and impact to pre-existing data solutions and projects underway
- Manage multiple relationships across the organisation, including senior leaders, and at times with, external parties
- Act as a liaison between business leaders and stakeholders to gather information, share best practices, and ensure initiatives are executed appropriately
- Support development of material to socialise the use and benefits of data modelling to a range of stakeholders with varying data / technical understanding and seniority
Must Have:
- Strong interpersonal skills, tact, patience, courtesy, good listening skills, team player
- Asset management experience/knowledge and industry specific data models
- Strong experience as a senior data architect, producing data models and business diagrams to explain complex issues
- Strong understanding of modern data platform concepts such as Data Lake, Lakehouse, and Data Warehouse.
- Strong experience in key data sets covering Front, Middle and Back Office functions
- Experience of complex and large change projects and analysis of the end-to-end data flows and the operating model
- Expertise in eliciting, analysing, prioritising and validating requirements and building partnerships with business stakeholders
- Produce high quality requirements and architecture documentation, business process and data flows and current and target states
- Experience of assimilating a lot of detailed information, identify the important points and present them in the appropriate format
- Experience of leading and facilitating effective project meetings & workshops
- Proven track record in designing and delivering business solutions
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”
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