Data Architect
3 weeks ago
Key accountabilities include :
- Subject matter expert on the Data Value Stream Enabler which contains data architecture current state, future state, and roadmap for the transition.
- Collaborate with stakeholders across various value streams to understand their requirements, data architecture plans and ensure alignment with Data Value Stream
- Lead and own the development and implementation of architecture strategy and standards pertinent to the domain.
- Establish Standards and Best practices – Develop / introduce, and enforce new practices, processes, operating model, techniques, products, services, technologies, and standards where needed against identified use cases, via the appropriate governance bodies.
- Develop Reference Architecture – Create and maintain comprehensive data architecture reference models that serve as a blueprint for all data related initiatives across the bank.
- Develop and maintain comprehensive enterprise-level data models that drive the application models. Ensure that the models align with overall data architecture strategy and support seamless integration and interoperability of data across the bank.
- Act as the recognised technical expert associated with the relevant domain/systems.
- Accountable design authority for technology decisions and leadership of the appropriate governance bodies
- Stay abreast of technology trends and advise Technology and the business about potential benefits/impacts.
- Provides motivational leadership, sets team performance expectations, and monitors progress.
- Overall responsibility for supervising a department or a business unit/area team or manages delivery for most complex assignments.
Leadership & Teamwork
Key leadership and teamwork responsibilities include, but are not limited to:
- Provides motivational leadership and support, helping to drive pod performance, and monitor progress.
- Overall responsibility for supporting the team, managing delivery for complex assignments.
- Excellent communication and collaboration skills, with the ability to engage effectively with stakeholders at all levels.
- Collaborate with stakeholders across various value streams to understand their requirements, data architecture plans and ensure alignment with Data Value Stream
Functional Knowledge
- Ability to align the data architecture with the business strategies and objectives.
- Ability to assess and recommend new technologies and practices.
- Data Architecture and Modelling: Expertise in data architecture principles, methodologies, and tools. Proficient in creating and managing enterprise data models.
- Knowledge on industry recognized frameworks such a TOGAF and BIAN is preferred, though not mandatory.
- Data Change Management - Skills required to understand, plan, implement and communicate change effectively. The types of change can be relatively broad, and include organisational, technology, data, or process changes. Data Change Management will typically work extensively with other teams to assemble the expertise required to deliver a given outcome, though with direct accountability for:
- Decision-making to plan and implement the change.
- Understand and shape the change required.
- Governance support to ensure change is communicated, adheres to best practices and evidence decision-making appropriately.
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