Senior Data Engineer
ABOUT THE ROLE
We are seeking a Data Analyst to support the APAC Claims Operations team across 11 markets. This role is central to how the function monitors performance, identifies trends and makes decisions - and will work directly with senior leadership to deliver actionable insights from complex, multi-system data environments.
KEY RESPONSIBILITIES
BAU Reporting and Data Management
Produce, maintain and automate regular BAU reports covering claims volumes, financials, headcount and performance metrics across APAC markets.
Manage and reconcile data from multiple source systems, geographies and business lines, ensuring accuracy and consistency.
Identify, investigate and resolve data discrepancies, working with local market teams and IT as needed.
Maintain data documentation, version control and audit trails for all reporting outputs.
Ad Hoc Analysis
Respond to ad hoc data requests from senior leaders, including market-level deep dives, financial banding analysis and portfolio reviews.
Build and run queries across relational databases and data warehouses to extract and manipulate large datasets.
Translate ambiguous business questions into structured analytical frameworks with clear outputs.
Dashboard Development
Design, build, and maintain end-to-end automated reporting pipelines, interactive dashboard and visualisations for operational and leadership audiences.
Iterate on existing reporting tools based on stakeholder feedback, ensuring outputs remain relevant and usable.
Ensure dashboards are scalable across markets and can be updated efficiently as data sources evolve.
Automation & Productivity Improvement
Proactively identify repetitive, manual reporting processes across regional and local teams, replacing them with resilient, scheduled Python/SQL automation workflows.
Develop lightweight scripts, data parsers, and custom tools to eliminate manual data entry, reconcile discrepancies, and streamline cross-market data exchange.
Establish version control (Git), documentation, and data validation checks
AI and Emerging Technology
Leverage modern AI-assisted coding tools to accelerate script development, refactoring, and data problem-solving.
Design and pilot practical AI applications for claims operations, such as automated classification of unstructured claims notes, anomaly/fraud pattern detection, and document summarisation.
Champion AI-driven operational enhancements, staying abreast of practical advancements in LLMs, agentic workflows, and automated intelligence.
Apply AI and machine learning tools to enhance data processing, pattern recognition and predictive analytics within the claims function.
Identify opportunities to embed AI-assisted automation into existing reporting and analytical workflows, reducing manual effort and improving speed to insight.
Collaborate with the broader Claims Transformation agenda to pilot and scale AI use cases, including natural language querying, anomaly detection and document summarisation.
Stay current with developments in AI tooling relevant to data and operations, and bring forward practical recommendations for adoption.
Continuous Improvement
Proactively identify gaps in current data coverage or reporting processes and propose solutions.
Automate repetitive reporting tasks to improve turnaround time and reduce manual error.
SKILLS AND EXPERIENCE
Essential
3+ years in a Senior data analyst or similar role, preferably in financial services, insurance or a similarly complex operational environment.
Proficiency in Python or equivalent scripting/automation skills.
Strong SQL skills with experience querying multi-table relational databases.
Experience working with data from multiple systems, geographies or business units.
Proven ability to identify and resolve data quality issues with minimal supervision.
High proficiency in Excel, including pivot tables, complex formulas and data modelling.
Experience building dashboards using tools such as Power BI, Tableau or equivalent.
Practical experience using AI tools (e.g. LLMs, Copilot, AI-assisted coding or analytics platforms) to improve analytical output or workflow efficiency.
Desirable
Exposure to claims, actuarial or insurance data.
Experience working in or with APAC markets.
Experience with automated document/presentation generation (e.g., Python to PowerPoint/Email/PDF pipelines).
Understanding of financial reporting, including expense management or claims financials.
Experience with machine learning concepts or predictive modelling.
QUALIFICATIONS
Essential
Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics or a related quantitative discipline.
Desirable
Postgraduate qualification in a relevant field.
Professional certification in data or analytics (e.g. Microsoft Power BI Data Analyst, Google Data Analytics Certificate, AWS Certified Data Analytics).
Certification or coursework in AI or machine learning (e.g. Coursera ML Specialisation, DataCamp AI Fundamentals).
ATTRIBUTES
Proactive self-starter who identifies problems and acts before being asked.
Highly organised, able to manage multiple competing priorities to tight deadlines.
Comfortable operating in ambiguity and translating incomplete briefs into structured work.
Strong communicator who can present data clearly to both technical and non-technical audiences.
Curious about AI and new technology - willing to experiment and embed new tools into daily practice.
Detail-oriented without losing sight of the bigger picture.
Collaborative and responsive - works well across time zones and cultures.