Head of Enterprise Data Solutions (EDS)

Highlights

• Fixed bonus and performance bonus
• Hybrid Working and remote teaming
• Work from Anywhere
• Equality Welfare & Benefit (LGBTQA+)
• Global online training modules to personalized learning journey
• International Opportunities for Career Growth
• Community Support with Employee well-being resource groups

Job Description

Key responsibilities: (ordered by priority)

1. Lead the Enterprise Data Solutions (EDS) team in designing, developing, and maintaining data warehouses, data marts, and operational data stores.

2. Recommend and implement data architecture strategies that support business growth, agility, and resilience.

3. Oversee the creation of reports and dashboards for operational and analytical use, leveraging tools like QlikView and Power BI.

4. Support transformation programs such as SVOC, CRM, and CEP, ensuring timely and accurate data delivery.

5. Drive initiatives to improve data quality, availability, and scalability, including metadata management and lineage tracking.

6. Collaborate with the Data Governance and Security teams to ensure compliance with PDPA, internal governance, and data privacy standards.

7. Architect and optimize data pipelines using Talend, SSIS, and other ETL tools to ensure scalability and performance.

8. Manage vendor relationships and participate in RFP evaluations for data-related platforms and services.

Qualifications:

Hard Skills: (Ordered by priority)

1. Minimum 5-8 years of experience in data management, analytics, or enterprise architecture.

2. Proven expertise in DWH/star schema development and data architecture.

3. Proficient in SQL, especially MSSQL (T-SQL).

4. Familiarity with insurance industry data flows and IFRS17 compliance is a plus.

5. Hands-on experience with ETL tools (Talend, SSIS) and BI platforms (QlikView, Power BI).

6. Strong experience in business process modeling and logic design.

Soft Skills: (Must have)

1. Experience managing small data teams (510 people) and cross-functional collaboration.

2. Good command of English and strong communication skills.

Preferred Skills: (Ordered by priority)

1. Knowledge of cloud-based data platforms (e.g., AWS, Azure).

2. Experience with data governance frameworks and metadata management.

3. Exposure to AI/ML integration in data pipelines and analytics.

4. Understanding of regional transformation strategies and centralized intelligence hubs.