{"id":179673,"url":"https://alion.io/job/chubb-senior-data-engineer","title":"Senior Data Engineer","company":{"id":18935,"name":"Chubb","domain":"chubb.com","url":"https://alion.io/company/chubb","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":84,"open_postings":98,"ghost_share":0,"stale_share":0.837,"repost_share":0,"time_to_fill_p50_days":9,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Kuala Lumpur, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":15000,"max_usd":39000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2491},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Copilot","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"AWS","optional":true}],"status":"closed","first_seen_at":"2026-08-31T00:00:00Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-10-21T15:39:32Z","board_verified":false,"closed_at":"2026-10-21T15:39:32Z","days_open":51,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":51},"description":"ABOUT THE ROLE\nWe 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.\nKEY RESPONSIBILITIES\nBAU Reporting and Data Management\nProduce, maintain and automate regular BAU reports covering claims volumes, financials, headcount and performance metrics across APAC markets.\n\nManage and reconcile data from multiple source systems, geographies and business lines, ensuring accuracy and consistency.\n\nIdentify, investigate and resolve data discrepancies, working with local market teams and IT as needed.\n\nMaintain data documentation, version control and audit trails for all reporting outputs.\n\nAd Hoc Analysis\nRespond to ad hoc data requests from senior leaders, including market-level deep dives, financial banding analysis and portfolio reviews.\n\nBuild and run queries across relational databases and data warehouses to extract and manipulate large datasets.\n\nTranslate ambiguous business questions into structured analytical frameworks with clear outputs.\n\nDashboard Development\nDesign, build, and maintain end-to-end automated reporting pipelines, interactive dashboard and visualisations for operational and leadership audiences.\n\nIterate on existing reporting tools based on stakeholder feedback, ensuring outputs remain relevant and usable.\n\nEnsure dashboards are scalable across markets and can be updated efficiently as data sources evolve.\n\nAutomation & Productivity Improvement\nProactively identify repetitive, manual reporting processes across regional and local teams, replacing them with resilient, scheduled Python/SQL automation workflows.\n\nDevelop lightweight scripts, data parsers, and custom tools to eliminate manual data entry, reconcile discrepancies, and streamline cross-market data exchange.\n\nEstablish version control (Git), documentation, and data validation checks\n\nAI and Emerging Technology\nLeverage modern AI-assisted coding tools to accelerate script development, refactoring, and data problem-solving.\n\nDesign and pilot practical AI applications for claims operations, such as automated classification of unstructured claims notes, anomaly/fraud pattern detection, and document summarisation.\n\nChampion AI-driven operational enhancements, staying abreast of practical advancements in LLMs, agentic workflows, and automated intelligence.\n\nApply AI and machine learning tools to enhance data processing, pattern recognition and predictive analytics within the claims function.\n\nIdentify opportunities to embed AI-assisted automation into existing reporting and analytical workflows, reducing manual effort and improving speed to insight.\n\nCollaborate with the broader Claims Transformation agenda to pilot and scale AI use cases, including natural language querying, anomaly detection and document summarisation.\n\nStay current with developments in AI tooling relevant to data and operations, and bring forward practical recommendations for adoption.\n\nContinuous Improvement\nProactively identify gaps in current data coverage or reporting processes and propose solutions.\n\nAutomate repetitive reporting tasks to improve turnaround time and reduce manual error.\n\nSKILLS AND EXPERIENCE\nEssential\n3+ years in a Senior data analyst or similar role, preferably in financial services, insurance or a similarly complex operational environment.\n\nProficiency in Python or equivalent scripting/automation skills.\n\nStrong SQL skills with experience querying multi-table relational databases.\n\nExperience working with data from multiple systems, geographies or business units.\n\nProven ability to identify and resolve data quality issues with minimal supervision.\n\nHigh proficiency in Excel, including pivot tables, complex formulas and data modelling.\n\nExperience building dashboards using tools such as Power BI, Tableau or equivalent.\n\nPractical experience using AI tools (e.g. LLMs, Copilot, AI-assisted coding or analytics platforms) to improve analytical output or workflow efficiency.\n\nDesirable\nExposure to claims, actuarial or insurance data.\n\nExperience working in or with APAC markets.\n\nExperience with automated document/presentation generation (e.g., Python to PowerPoint/Email/PDF pipelines).\n\nUnderstanding of financial reporting, including expense management or claims financials.\n\nExperience with machine learning concepts or predictive modelling.\n\nQUALIFICATIONS\nEssential\nBachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics or a related quantitative discipline.\n\nDesirable\nPostgraduate qualification in a relevant field.\n\nProfessional certification in data or analytics (e.g. Microsoft Power BI Data Analyst, Google Data Analytics Certificate, AWS Certified Data Analytics).\n\nCertification or coursework in AI or machine learning (e.g. Coursera ML Specialisation, DataCamp AI Fundamentals).\n\nATTRIBUTES\nProactive self-starter who identifies problems and acts before being asked.\n\nHighly organised, able to manage multiple competing priorities to tight deadlines.\n\nComfortable operating in ambiguity and translating incomplete briefs into structured work.\n\nStrong communicator who can present data clearly to both technical and non-technical audiences.\n\nCurious about AI and new technology - willing to experiment and embed new tools into daily practice.\n\nDetail-oriented without losing sight of the bigger picture.\n\nCollaborative and responsive - works well across time zones and 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