Data Architect

Job description:

The Data Architect is responsible in defining the equivalent technical data strategy in conjunction with the business vision and defined outcomes. The role is responsible in building and managing a company's enterprise data architecture and creates strategies in modernizing and expanding the enterprise's data landscape to improve efficiency and provide authorized end users with consistent and reliable access to key data. The Data architect also supports business initiatives to ensure the enterprise follows best practices for data standards and data management.

Responsibilities:

1. Data Architecture Design:

2. Develop and maintain enterprise data models, data standards, and data governance practices.

3. Create and maintain data architecture documentation, including conceptual, logical, and physical data models.

4. Data Strategy and Governance:

5. Define data strategy, ensuring it aligns with business objectives and regulatory requirements.

6. Co-lead the execution of the formulated Data Strategy, and anything which will be cascaded by Corporate and Regional Offices
7. Co-create data roadmaps and target data architecture for the organization and coordinate with project managers and other cross-functional teams on their implementation
8. Keep Sun Life Philippines aligned to RO and Corporate data management and architecture principles and technologies
9. Establish and enforce data governance policies, procedures, and best practices.

10. Participate in IT project reviews to ensure alignment to data management best practices

11. Data Solutions and Integration:

12. Design data solutions for key projects, ensuring efficient data flows and integrations across platforms.

13. Oversee data migrations, data lakehousing, and ETL processes.
14. Provides expertise in formulating solutions around Data and interfacing systems, which are dependent on our data architecture and landscape.

15. Provides expert advise on improvements on algorithms, data transformation and loading methodologies, data management, and the like - bringing in new approaches and technologies, from outside experience.

16. Stakeholder Engagement:

17. Collaborate closely with different business units including, but not limited to, BI and Data Analytics, Operations, Marketing teams to understand their data requirements and design solutions to address them

18. Work closely with IT teams, including application developers, database administrators, and security teams.

19. Technical Leadership:

20. Provide guidance and mentorship to data engineers and analysts.

21. Acts as SME for data management and integration technology and guide delivery teams on implementing data solutions
22. Stay updated on the latest data technologies and trends, recommending improvements where appropriate.

23. Lead the organization in adopting emerging modern data technology including cloud databases, NoSQL and NewSQL data stores, modern data integration patterns, Cloud Data Lakehouses

24. Compliance and Security:

25. Ensure data architecture complies with data privacy regulations and security best practices.

Qualifications:

Education:

• Bachelor's degree in Computer Science, Information Technology, or a related field.

Experience:

• At least 10 years of experience in data architecture, data modeling, and data management.
• Strong experience with data platforms (e.g., SQL, NoSQL, cloud databases).
• Experience with data governance and data privacy regulations.

Technical Skills:

• Proficiency in data modeling tools (e.g., Erwin, PowerDesigner).
• Experience with cloud platforms (e.g., AWS).
• Familiarity with data integration tools (e.g. Amazon DMS, AWS Glue, Informatica Cloud Data Integration) and ETL processes.
• Knowledge of data security practices and compliance standards.
• Experience in leading and mentoring data development teams (BI, Data Integration, Data Quality)
• Working knowledge of modern data platforms and practices including Data Engineering, Big Data and/or Data Lake, Cloud Data Warehouses, Data Streaming
• Extensive experience implementing Data Warehouses, ETL pipelines, creation of Data Models
• Knowledge of data management functions including Data Catalog/Metadata Management, (e.g. AWS Glue Data Catalog), Data Quality (e.g. Informatica Cloud Data Quality) and Master Data Management (Informatica C360) and of technology platforms that can support them
• Background in Business Intelligence and Data Analytics practices
• Ability to articulate solution design and architecture, differences between different types of data stores implementation, functions of data technologies, etc. and present them to technical and business stakeholders including the C-suite, regional, and global counterparts.
• Working knowledge in Data Lakehouse powered by Apache Iceberg and medallion architecture
• Working knowledge in delivering data products through API
• Experience in participating in Data Governance activities
• Experience implementing data solutions in the cloud. Certification is preferred (e.g. AWS)

Soft Skills:

• Strong communication and stakeholder management skills.
• Ability to work in a collaborative, fast-paced environment.
• Problem-solving and analytical mindset.