Financial System Analyst - Data (Banking)

Scope of the Role

You will be responsible for end-to-end delivery of enterprise data and analytics solutions, leveraging both traditional and modern data architectures.

The role covers the full lifecycle—from requirements analysis and solution design to testing, implementation, and production support—ensuring scalable, high-quality, and compliant data platforms that enable advanced analytics and AI initiatives.

Experience in Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision Systems, and Retail/Wholesale Data Marts will be a strong advantage.

Key Responsibilities

• Lead end-to-end delivery of data & analytics solutions across the SDLC
• Analyze business and regulatory requirements; translate them into scalable architecture and design solutions
• Communicate complex technical concepts to business and senior stakeholders in a simplified manner
• Review and approve test strategies, validation frameworks, and data quality controls
• Manage risks, issues, and regulatory commitments related to data and delivery timelines
• Participate in RFPs, PoCs, and platform/tool evaluations (Data, Analytics, AI)
• Collaborate with production support teams for root cause analysis and preventive controls
• Drive innovation and modernization initiatives (data cataloging, governance, AI enablement)
• Improve productivity, efficiency, and quality across delivery processes
• Design data architectures supporting NLP and AI-driven analytics

Technical Skillsets

Certifications

• Minimum 2 relevant certifications in Data, Cloud, or Analytics technologies

Data Platforms & Architecture

• Open table formats: Apache Iceberg, Delta Lake, Apache Hudi
• Distributed engines: Apache Spark, Trino/Presto, Hive
• Cost optimization: Tiered storage, lifecycle management, workload governance

Programming & Analytics

• Strong in SQL, BTEQ, GCFR
• Python (Pandas, NumPy)
• BI tools: Power BI, Qlik Sense

Data Integration & Quality

• Informatica (PowerCenter, BDM, IDQ, Enterprise Data Catalogue)
• Data ingestion: Batch, CDC, Streaming
• Data quality, validation & reconciliation frameworks

Governance, Risk & Compliance

• Data modelling & regulatory reporting
• Fine-grained access controls (row/column-level security, masking)
• Metadata, lineage, and impact analysis
• Regulatory frameworks: BCBS 239, MAS, AML/CFT

Big Data Platforms

• Cloudera Hadoop ecosystem: Hive, Impala, Spark, Iceberg, Trino

Functional Skillsets

Analytics Domains

• Financial Crime Analytics: Transaction Monitoring, KYC/CDD, Sanctions Screening
• Finance & Credit Risk Analytics: Reconciliation, performance management, regulatory reporting, IFRS9, Basel, credit risk exposure, NPL

Enterprise Data & Analytics

• Experience delivering large-scale analytics platforms across structured, semi-structured, and unstructured data
• Strong in requirements analysis and functional design for complex analytics use cases
• Expertise in data governance, lineage, and reconciliation frameworks

Unstructured Data & NLP Analytics

• Design data architectures for unstructured and semi-structured data ingestion and governance
• Experience with NLP use cases:
• Text classification & categorization
• Entity & relationship extraction
• Risk indicator detection
• Case/alert summarization