Enterprise Data and Analytics – System Analyst

Role Overview:

Responsible for end-to-end delivery of enterprise data and analytics solutions across traditional and modern data architectures. The role covers requirements analysis, solution design, testing, implementation, and production support, ensuring scalable, compliant, and high-quality data platforms that support advanced analytics and AI initiatives.

Experience in Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision Systems, and Retail & Wholesale Datamarts is advantageous.

Key Responsibilities:

• Total Yrs. of Experience 8-12 years System Analysis

• Lead end-to-end solution delivery across the full SDLC

• Analyze business and regulatory requirements and translate them into scalable solution designs with estimations

• Communicate complex technical and architectural concepts to business and senior stakeholders

• Review and approve test strategies, functional test cases, and data validation approaches

• Manage risks and issues related to scope, data quality, regulatory commitments, and timelines

• Participate in product/platform evaluations (RFPs, PoCs) for data, analytics, and AI tools

• Collaborate with production support for root cause analysis, resolution, and preventive controls

• Drive innovation and modernization initiatives including data governance, cataloguing, and AI enablement

• Improve productivity, efficiency, and quality across delivery and operations

• Design data architectures supporting NLP and AI-driven analytics

Functional Skillsets:

Analytics Domains:

• Financial Crime Analytics (Transaction Monitoring, CDD, Sanctions & Payments Screening)

• Finance & Credit Risk Analytics (Reconciliation, Reporting, Credit Risk, Basel, IFRS9)

Enterprise Data & Analytics:

• Experience delivering large-scale analytics platforms across structured, semi-structured, and unstructured data

• Strong requirements analysis and functional design for analytics use cases involving transactional and textual data

• Experience in data quality, governance, lineage, and reconciliation

Unstructured Data & NLP Analytics:

• Design data architectures for unstructured and semi-structured data ingestion and governance

• Translate business needs into NLP use cases such as text classification, entity extraction, risk identification, and summarization

Knowledge Graph & Relationship Analytics:

• Define relationship taxonomies, entity resolution rules, and linkage logic

• Design analytics for network-based risk identification, hidden associations, and exposure analysis

Technical Skillsets:

Certifications:

• Minimum two relevant certifications in data platforms, cloud, or analytics

Data Platforms & Architecture:

• Apache Iceberg, Delta Lake, Apache Hudi

• Spark, Trino/Presto, Hive

• Cost optimization (tiered storage, lifecycle management, workload governance)

Programming & Analytics:

• SQL, BTEQ, GCFR

• Python (Pandas, NumPy)

• Power BI, QlikSense

Data Integration & Quality:

• Informatica (PowerCenter, BDM, IDQ, Enterprise Data Catalogue)

• Batch, CDC, and streaming ingestion

• Data validation, quality, and reconciliation frameworks

Governance, Risk & Compliance:

• Data modelling, regulatory reporting

• Data access controls (row/column level, masking)

• Metadata management, lineage, impact analysis

• Compliance: BCBS 239, MAS, AML/CFT

Big Data Platforms:

• Cloudera Hadoop (Hive, Impala, Spark, Iceberg, Trino)