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Responsible for performing data analyses, running various mathematical calculations, generate production reports and interactive visualizations, so that an actionable insight can be delivered to relevant decisions makers internally and externally with good quality in a timely manner. Working closely with Data Governance and Data Management team to improve existing processes and accountable for translating business requests to technical requirements.

Your Day at Allianz Ayudhya

Support from lead data engineer, define and develop robust data transformation pipelines that met the Allianz standard on data platforms using PL/SQL, T-SQL, and ETL tools (e.g. Data stage). This may include data mart, staging database, or ETL extraction from multiple source systems (e.g. Oracle, Azure Synapse). Develop report/dashboard to support management/business unit by using BI tools such as SSRS, Cognos and Power BI. Co-lead business meetings, support in identifying key objective from stakeholders and translate objective to user requirements and bridge the gaps between business and technical knowledge within the departments. This shall at the end serve as core data catalogues that allow a self-service data analysis for business users. Provide in-depth and insightful analysis on trends and business drivers as well as root cause analysis on internal and external data to answer specific business questions and identify opportunities for improvement / automation. Responsible for quality of output, service delivery standards and operations standards. Ensure that the definition is aligned with OE governance as well as automated checks are in place. Monitoring daily job, debug issues and providing maintenance support. Support ad-hoc requests from internal and external users such as Allianz Asia Pacific or Allianz Group. Working closely with control functions such as security, risk, compliance, audit and governance team to ensure the gaps can be closed according to the request in the agreed schedule.

Must Have

Degree in Mathematics, Statistics, or Computer Science with major in Statistics At least 2 years’ experience as a data analyst, BI, data engineer, developer, or related fields

Nice to Have

Experience in Banking or Insurance is a big plus Experience of handling projects from requirements stage to go-live is a plus Strong hands-on experiences with SQL (of any dialects) Working experience in handling complex and large amounts of data Good written and spoken English

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