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.