TDM support for Compliance Data Analytics Portfolio

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