Data Architect
Main Purpose of Job:
- To design and implement a robust data architecture that aligns with the organisation's strategic goals.
- Create the blueprint for data systems, ensuring accuracy, accessibility and security.
- Develop the architecture in line with evolving business requirements.
- Provide integration assistance services to OpCo's wishing to integrate with the core dataset
Key Responsibilities:
Designing Enterprise Data Management Frameworks
- Develop and implement an overall organizational data strategy aligned with business processes.
- Design and manage end-to-end data architecture solutions, including data models, databases, and data warehouses.
- Establish frameworks to track data assets, usage, and integration.
- Align data architecture with strategic goals of the Group.
Ensuring Data Security and Compliance:
- Guarantee data security by implementing access restrictions, encryption, and privacy measures.
- Ensure compliance with regulations and industry standards.
Implementing Data Management Processes:
- Monitor system health, define relevant KPIs, and suggest improvements.
- Identify bottlenecks and enhance data infrastructure agility.
Building Data Models and Strategies:
- Translate business requirements into technical specifications.
- Work with large datasets, perform data mining, and create predictive models.
Reporting, Relationships & Management:
- Collaborate closely with stakeholders, including business analysts, data engineers, and developers.
- Collaborate across departments and communicate complex ideas clearly.
- Works closely with any required third party partners, establishing effective partnerships and well defined ways of working ensuring that any solutions developed are in line with the Digital Strategy
Qualifications & Experience:
- Degree or equivalent qualification in a relevant discipline such as Data Science, Information Technology or Computer Science
- At least 5 years in data architecture, data modelling or database design.
- Deep understanding of database design principles, data modelling, and data warehousing.
- Familiarity with SQL, NoSQL databases, big data technologies, and cloud storage solutions.
- Formal architecture design methods such as TOGAF
Technical, Training & Skill Levels:
- Knowledge of database management systems (SQL, NoSQL).
- Proven experience of data modelling and architecture design.
- Knowledge of programming languages (e.g., SQL, Python, Java).
- Knowledge of big data platforms and cloud solutions.
- Analytical skills such as critical thinking, problem-solving, and working with large datasets.
- Proficiency in data mining and predictive modelling.
- A solid understanding of existing and emerging data technologies
- In-depth knowledge of the principles and practices of good systems design
- Innovative thinking to devise solutions that address the gap between business needs and technological constraints.
- Excellent communication skills to effectively translate sophisticated concepts into easily understandable language