1. Job purpose
The Master Data Modeler's role is to design, implement, and document data architecture and data modeling solutions for the Greenfield,
which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise information management,
business intelligence, machine learning, data science, and other business interests.
2. Key accountabilities
1. Responsible for analyzing and translating business needs into data models supporting long-term solutions.
2. Work with business and application/solution teams to create data strategies, build data flows, and develop conceptually
3. Create logical and physical data models using best practices to ensure strong data structure and reduced redundancy.
4. Optimize and update logical and physical data models to support new and existing projects.
5. Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
6. Recommend opportunities for reuse of data models in new environments.
7. Evaluate existing data systems and perform reverse engineering of physical data models from databases and SQL scripts.
8. Review modifications of existing systems for cross-compatibility.
9. Maintain metadata and evaluate data models for variances and discrepancies.
10. Analyze data-related system integration challenges and propose appropriate solutions
11. Work proactively and independently to address project requirements and articulate issues/challenges to reduce project
12. Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best
13. Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data
14. Ensure TSRM Data Security Compliance. Ensure best practices are applied to make sure authentication, data protection,
encryption (in rest and in motion), and overall security is applied to production deliveries.
15. Validate compliance with TRA, Government, and company data management policies and practices in order to minimize
16. Handling escalations, prioritizing projects and team activities, while proactively identifying areas of improvement which
best benefit the business.
3. Qualifications, experience, skills, and competencies
Total work experience to be at least 10 years.
Experience (at least 4 years) in a similar capacity (preferably within a Telco). Proven experience leading technical teams.
Extensive experience in data modeling, and related tools (Erwin or ER Studio, or others).
Strong record in building data models across different data layers and platforms.
Experience in Data Warehouse & Database Management System (DBMS) with a strong understanding of Data Management
solutions especially: Teradata, Informatica, SQL Server, Oracle.
Strong background in Big Data platforms such as Cloudera and Hortonworks.
Good understanding of the main components in any Hadoop deployment (HDFS, YARN, NoSQL databases, data access
components, workflow scheduling, cloud management, and monitoring, etc).
Good background in business intelligence tools and technology.
Good background in predictive modeling, machine learning, and data mining.
Excellent analysis and problem-solving skills.
Minimum Bachelor in Information Technology/ Information Services/ Computer Science
Master’s degree is a plus
Certifications such as e-TOM, TOGAF, ISO, ITIL, etc. is a plus
Knowledge and skills:
Good communication and interpersonal skills.
Excellent command of the English language.
Excellent technical management, team leading, and influencing skills.
Excellent analytical skills. Precise and thorough.
Respectful of deadlines.