MIS Team Lead (Life Insurance) - Phillip Life Assurance Public Company Limited

Data Platform Design & Architecture

• Design, develop, and maintain a scalable data platform covering application data layers, data staging, data warehouse, and data models.
• Define and implement data architecture standards, data governance policies, and best practices for data quality and integrity.
• Evaluate and recommend modern data technologies and cloud-based solutions aligned with business growth objectives.

ETL Development & Data Operations

• Develop, optimise, and maintain ETL/ELT pipelines to extract, transform, and load data from multiple source systems into the data warehouse.
• Write and optimise complex SQL queries to extract, validate, and deliver data based on business requests and reporting needs.
• Monitor data pipeline health, troubleshoot failures, and ensure timely data availability for downstream consumers.

Business Intelligence & Dashboarding

• Design and build interactive business dashboards and dynamic reports that enable business teams to drive strategy and production decisions.
• Collaborate with business stakeholders to translate requirements into actionable BI solutions and self-service analytics capabilities.
• Ensure data visualisations are accurate, insightful, and aligned with key performance indicators (KPIs).

AI Readiness & Advanced Analytics

• Drive the competency and potential of AI initiatives by curating and structuring foundational data building blocks for machine learning and analytics use cases.
• Partner with data scientists and business analysts to ensure data assets are AI-ready, well-documented, and accessible.
• Identify opportunities to apply AI/ML models to enhance business intelligence, automate processes, and generate predictive insights.

Collaboration & Mentorship

• Serve as a technical lead and mentor to junior data engineers, fostering a culture of continuous learning and engineering excellence.
• Work cross-functionally with IT, actuarial, underwriting, marketing, and operations teams to align data solutions with business objectives.

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, Data Engineering, or a related field.
• Minimum 7 years of experience in data engineering, ETL development, or data platform architecture.
• Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MS SQL Server).
• Hands-on experience designing and building data warehouses, data lakes, and dimensional data models (Star/Snowflake schemas).
• Proficiency with ETL/ELT tools and frameworks (e.g., Apache Airflow, Informatica, Talend, dbt, or equivalent).
• Experience with BI and visualization tools such as Power BI, Tableau, Looker, or Apache Superset.
• Experience with cloud data platforms (e.g., AWS, Azure, GCP) and modern data stack technologies would be an advantage but not necessary
• Working knowledge of Python or other scripting languages for data processing and automation.
• Understanding of AI/ML concepts and the ability to prepare and structure data for advanced analytics use cases.
• Strong analytical, problem-solving, and communication skills with the ability to work effectively across teams.

Preferred Qualifications:

• Experience in the insurance or financial services industry.
• Knowledge of data governance frameworks and data cataloguing tools.
• Familiarity with real-time data streaming technologies (e.g., Kafka, Spark Streaming).