Assistant Vice President, Data Engineering and Analytics

1 month ago


Malaysia Generali Malaysia Full time

Job Scope / Position Summary

The AVP, Data Engineering and Analytics plays an important role within the organization, responsible for es-tablishing a "Data Centre of Excellence" to identify and promote data-driven opportunities, supporting the business development of Generali Insurance Malaysia Berhad.

The candidate should have a technical background with hands-on experience and expertise in AWS services necessary to maintain and enhance the existing Data Lake.

Main Responsibility

1. Manage Data team (Data Analyst, Data Engineers, Data Scientist, etc.).

• Manage and support internal resources in their growth and perform assessment and contracting of external consultants.

• Manage team activities for projects & BAU and ensure that deliverables are meeting business requirement and delivered on time and budget.

• Put in place team meetings and ceremonials monitor activities and insure information sharing.

• Encourage innovation and Devops excellence to reach ambitious objectives on SLA and business value.

2. Extraction, modelling and sharing of data assets.

• Interact with source systems’ owners to setup automated and optimize data extractions and replications.

• Maintain and optimize ETL and/or Replication tools to automatically load data in the Cloud data lake.

• Define & implement data model to structure and prepare data for reporting & analytics.

3. Design, creation, and maintenance of reporting and analytical capabilities.

• Maintain and support the current SAP BI reporting platform.

• Define a new innovative solution for Reporting and analytics that meet new business requirements and aligned with Generali standards.

• Support the migration from the current SAP BI reporting platform to the new target solution

4. Collaboration and training of users on data platforms:

• Identify and cartography data users and data usages across departments.

• Perform training in various Data tools.

• Relay group awareness and cultural events.

• Communicate on data initiatives to improve global data awareness

5. Support Data Governance and portfolio of initiatives.

• Support Data Governance Committee to steer data strategy and report progress with necessary KPIs.

• Define priorities aligned with business objectives and ensure key success factors are addressed for current and future need of the organization for:

o Finance, Underwriting, Claim, Marketing, Sales, Actuarial, etc.

o Local regulatory /BNM and group reporting requirements

• Maintain road map and initiatives planning.

• Maintain necessary documentation about initiatives (objectives, solutions, owners, risks, KPIs …)

6. Collaborate with Generali data community:

• Collaborate with the Generali Data community to align data initiatives with group and regional requirements and directions.

• Encourage collaboration across communities of data (engineers, analysts, stewards, …).

• Contribute to overall data maturity improvement of Generali, sharing best practices, new technologies & approaches.

7. Deploy a Data Management and Data Quality Framework.

• Define Data Governance framework and processes in alignment with the company Data.

8. Governance Policy and Guidelines.

• Supporting new projects (including non-data projects) in the adoption of framework.

• Supporting data stewards on complex data management activities (i.e. Data Quality Monitoring).

• Run data cleansing and data quality improvement initiatives for continuous improvements of data quality in the organization.

• Support Master Data Management and Customer Data platform initiatives.

Qualification and Experience Requirement

• Bachelor/ Master’s degree in relevant discipline.

• Minimum of 8 years of hands-on experience of data engineering and analytics in a corporate or consulting setting.

• Exposure to the General Insurance industry is a plus.

• Requires strong technical skills and background – IT, engineering, computer science, coupled with the ability to code design, develop, and deploy applications using advanced unstructured and semi-structured data analysis techniques and utilizing high-performance computing environments.

• Hands-on Experience in AWS S3, Glue, EMR, Redshift, Lambda, Sagemaker.

• Hands-on Experience in SQL, python, spark and pyspark coding.

• Hands-on Experience with SAP BI 4.2 or similar reporting tools.

• Strong analytical/interpersonal/communication skills.

• Ability to express complex technical concepts effectively, both verbally and in writing.

• Ability to work well with people from many different disciplines with varying degrees of technical experience.

• Good understanding of Data Management, Data Governance, Data quality and Data Documentation concepts.

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