Job Description

Key Responsibilities - Architecture & Strategy

- Contribute to enterprise data architecture strategy and regulatory needs. - Architect end-to-end data platforms supporting traditional BI, advanced analytics, AI/ML, and real-time insights. - Define data analytics solution adapting concepts like Lakehouse, Data Mesh, Data Fabric while adopting cloud native data & AI services and modern integration patterns. - Work on banking-grade platforms including Teradata, Cloudera, Qlik, Microsoft Power BI and other enterprise data analytics tools.

Key Responsibilities - Solution Design & Delivery

- Build and maintain enterprise data platforms leveraging open-source technologies ranging data integration, data base, visualisation, modelling, APIs/micro services - Lead design and delivery of analytical applications leveraging enterprise Data Analytics platforms (dashboards, predictive models, reporting suites, self-service and operational analytics) - Build and operationalize Data products, AI/ML solutions for banking use cases such as next best offer, fraud detection, customer segmentation, credit scoring, and risk modelling etc. - Architect and develop data pipelines, APIs, and data serving layers for production-grade analytics. - Deploy best practices in Data Ops, ML Ops and integration with regulatory-compliant systems. - Define enterprise design principles, security and control standards

Key Responsibilities - Team & Leadership -

Plan technical deliverables (including any system enhancements and upgrades) to meet project's requirements within allocated budget and schedule. - Plan & collaborate across different application teams to manage technical dependencies of the solution - Provide status update related to technical delivery to Project Manager (PM) - Partner with System Analysts and Business Solution Specialist to collate, understand and finalize functional and technical requirements - Partner with test Manager for delivery through SIT, UAT, performance / load testing and application security testing with quality results- Manage technical implementation plan across application teams - coordinate technical implementation activities across application teams to ensure non-event production cutover and adequate post implementation support - Escalate issues that impacts project schedule on timely basis and propose workarounds/resolutions - Lead and mentor cross-functional teams of data engineers, BI developers, data scientists, and ML engineers. - Establish engineering standards, DevOps/MLOps pipelines, and governance for data analytics applications - Collaborate closely with business leaders, ensuring technical solutions meet business goals and compliance standards.

Required Skills & Experience

- Proven experience in architecting and delivering enterprise-scale data & analytics platforms for banking.

Areas of interest are: - Strong grasp of banking operations, risk, compliance, fraud, and customer analytics. - Strong experience in driving transformation of Finance Data Platform, Regulatory Reporting (MAS, PRA, HKMA), Capital Reporting (RWA), Liquidity Reporting (LCR, NSFR, CFMR), Basel IV, Financial Reconciliation - Expertise in Risk & Compliance areas: Credit Risk Analytics, Enterprise Risk Reporting, AML & Financial Crime Compliance, Trade Surveillance Analytics, Data Quality & Controls, BCBS239 Data Governance - Expertise in Wholesale Banking & Treasury, Treasury & Liquidity Analytics, Capital Markets Data, Trade Finance Reporting, FTP (Fund Transfer Pricing), Balance Sheet Management - Data Platforms: Teradata, Hadoop/Cloudera, Snowflake, Databricks, Lake House, Azure, Google, Huawei, Ali cloud - Delivery management experience managing governance committees, Benefits Realization, Budget Management, RAID / RACI Management, Resource Capacity Planning, Target Operating Model (TOM) - BI & Analytics Platforms: Teradata, Cloudera, Microsoft Power BI / Azure Analytics, Qlik. - AI/ML, Analytics: Spark Scala, Python, R, Java, TensorFlow, PyTorch, Data Ops tooling, MLflow, Kubernetes - Streaming & Integration: Kafka, Spark Streaming, Informatica, Talend. - Databases, Data federation: SQL, NoSQL DBs, Denodo, Snowflake - Cloud & DevOps: Kubernetes, Airflow, GitOps, CI/CD tools - Knowledge of statistical modeling, predictive analytics, NLP, and AI-driven decision systems. - Financial services data models & data modelling tools and data governance processes - Hadoop languages & tools - Spark, Python, R, Pig, Hue, Impala, Hive, Hbase, Informatica IDL - Experience with AI in banking regulatory contexts (model governance, explainability, audit readiness). - Exposure to data mesh, federated governance, and advanced BI/AI architectures. - 10+ years in data/analytics technology, with 5+ years in an architectural or leadership role. - Demonstrated ability to lead multi-disciplinary teams (engineering, BI, data science). - Excellent communication skills to influence C-level executives and business stakeholders.

JOB REQUIREMENTS - More than 15 years track record in developing and delivering global/regional IT capabilities for a multi national/regional company with annual budgetary responsibility - More than 5 years leadership experience in managing IT delivery teams - Experience in implementing large-scale project implementation - Proven result-oriented person with a focus on delivery