Data Analyst (Real Time), Enterprise Information Management

About the role

The Data Analyst supports the Bank's growing real-time data capability and needs. Focus on enabling near-real-time insights across customer, account, and transactions data to support business decision-making. You will work closely with both Data Engineering and Business teams to translate the data into meaningful insights and ensure data is accurate, timely and fit for use.

Responsibilities

• Real-Time Analytics & Insight Delivery
• Design and deliver near real-time analytical use cases (e.g. customer behavior, transaction monitoring, operational alerts)
• Translate streaming data into business-ready metrics, KPIs, and dashboards - Drive time-sensitive insights to support decision-making (fraud, campaigns, risk signals, etc.)
• Data Understanding & Modelling
• Define and maintain data models for real-time marts (customer, account, transaction)
• Ensure data is: Business-aligned o Consistent with EDW definitions (avoid conflicting metrics)
• Work closely with engineering teams to shape schema design for analytics usability
• Data Quality & Governance (Real-Time Context)
• Define data quality rules and validation logic for streaming data
• Monitor data anomalies and trigger root cause analysis (RCA)
• Ensure alignment with enterprise data governance standards, adapted for real-time constraints
• Use Case Development & Business Engagement
• Partner with business stakeholders to:
• Identify high-value real-time use cases
• Translate requirements into analytical logic
• Drive quick wins to demonstrate value of real-time data (important in early-stage maturity)
• Collaboration with Engineering & Platform Teams
• Work closely with:
• Real-time data engineers (Flink / Kafka / pipelines)
• Data platform teams (ClickHouse / HUDI / Hive)
• Ensure: Data is fit for consumption, and Latency vs accuracy trade-offs are clearly defined
• Performance & Optimization
• Optimize queries and analytical logic for low-latency environments - Ensure efficient usage of ClickHouse or equivalent real-time analytical engines
• Standardisation & Reusability
• Define reusable:
• Metrics definitions
• Analytical patterns
• Data contracts for real-time consumption
• Prevent fragmented logic across teams
• Leadership & Mentorship
• Act as subject matter expert (SME) for real-time analytics
• Guide junior analysts on:
• Real-time thinking (event-driven vs batch mindset)
• Data interpretation and storytelling
• Key Deliverables
• Real-time dashboards and analytical outputs
• Data mart definitions (customer/account/transaction)
• Data quality rules and monitoring framework
• Documented business metrics and logic
• Use case backlog and delivery roadmap
• Skills & Experience We Are Looking For:
• Experience - 1 - 2 years in data analytics / data domain
• Strong experience in:
• Banking / financial services (preferred)
• Data warehouse (EDW) and transition to real-time
• Exposure to streaming or near real-time environments is a strong advantage Technical Skills
• Strong SQL (mandatory)
• Experience with:
• Analytical databases (e.g. ClickHouse, BigQuery, Snowflake)
• Data modelling (dimensional / hybrid models)
• Familiarity with:
• Streaming concepts (Kafka, Flink, CDC)
• Data lake technologies (Hive, Hudi)
• Analytical & Business Skills Strong ability to:
• Translate business questions into data logic
• Interpret complex datasets into clear insights
• Experience in:
• Dashboarding
• Data storytelling
• Soft Skills (Critical for This Role)
• Able to operate in ambiguity and evolving environments
• Strong stakeholder management: Business, IT, Vendors
• Confident to challenge unclear requirements and/or misaligned metrics
• For more job opportunities, please go to HLB Careers: https://hlb.wd3.myworkdayjobs.com/HLBCareers/
• We appreciate your application and will be in touch with shortlisted candidates regarding next steps.
• About Hong Leong Bank
• Realise your full potential at Hong

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