Data Analyst (Real Time), Enterprise Information Management

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Overview:

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

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