Data Specialist

Under the guidance of more senior IT Data Architects, the IT Data Specialist applies data analysis, data modelling and quality assurance techniques based on a detailed understanding of business processes to establish, modify or maintain internal data structures and associated components (entity, relationship and attribute descriptions). They develop and maintain a formal description of the internal data and data structures of the business, which can include data definitions, data models, and data flow diagrams referred to as metadata.

The IT Data Specialist is a technologist with a good background in application and IT Data Architectures within the context of IT Enterprise Architecture. He or she has cross-domain level knowledge and attends to the data needs of internal clients, working across domains and/or functions. A critical skill required from an IT Data Specialist is the conversion and migration of medium-sized amounts of data from one database to another, whether implementing an entirely new enterprise application or consolidating, upgrading, or modernizing an existing one. A strong focus on data migration is essential to overall project success.

Core Areas of Focus

1. Automation Enablement
2. Drive and support Digital First strategy

Key Roles and Responsibilities

1. Optimise Data Management processes through identifying Automation opportunities.
2. Ensure that all enhancements adhere to the Data Governance Framework.
3. Drive service improvement initiatives to implementation.
4. Work closely with your business to identify issues and use data to propose solutions for effective decision-making.
5. Create clear reports that tell compelling stories about how customers or clients work with the business.
6. Drive implementation and adoption of Digital Strategy.
7. Attend to requests received from the business within the agreed timeframes.

Requirements

1. High School Certification.
2. ITIL V3 / 4 Foundation Certification.
3. At least 3 years of working experience in business analysis/informatics and business outcomes research within a fast-paced and complex business setting.
4. Experience in probability and statistics, time-series analysis, and machine learning methods (e.g., linear regression, correlation, statistical significance).
5. A minimum of 1 year’s experience in a similar role working on data warehouse projects with dimensional models.
6. Understanding of SAFe methodology.
7. Experience with Power BI for building dashboards for Data Visualisation & Reporting.
8. Skills and knowledge in Time Management, Autonomy, Problem solving, and logical thinking.