You will be responsible for end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture. Experience with Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision systems, Retail & Wholesale Datamarts will of advantage
The role spans requirements analysis, solution design, testing, implementation, and production support ensuring high-quality, scalable, and compliant data platforms that support advanced analytics and AI initiatives.
Key Responsibilities
- Lead end-to-end solution delivery for data and analytics across the full SDLC
- Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations
- Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner
- Review and approve test strategies, functional test cases, and data validation approaches
- Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines
- Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling
- Partner with production support team to conduct root cause analysis, resolution, and preventive controls
- Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement
- Drive productivity, efficiency & quality improvements across delivery and operational processes
- Ability to design data architectures supporting NLP and AI-driven analytics
Functional Skillsets
Analytics Domains
- Financial Crime Analytics Transaction Monitoring, Customer Due Diligence, Sanctions & Payments Screening
- Finance & Credit Risk Analytics Financial reconciliation, Allocation, Performance management, Regulatory and Management reporting, Credit risk exposure, NPL, Counterparty risk, Basel & IFRS9 input variables
Enterprise Data, Analytics & Unstructured Data Enablement
Proven experience delivering large-scale analytics platforms within financial services spanning structured, semi-structured, and unstructured data
- Strong capability in requirements analysis and functional design for analytics use cases involving Transactional data, Investigator narratives, Case notes and alerts, Policy & Customer communications documents
- Experience defining data quality, governance, lineage, and reconciliation controls for both structured and NLP-derived datasets
Unstructured Data & NLP-Enabled Analytics
- Ability to define data architectures and data flows that ingest, curate, and govern unstructured and semi-structured data within enterprise data platforms
- Experience translating business requirements into NLP-enabled analytical use cases, such as Text classification and categorization, Entity & relationship extraction, Risk indicator identification, Summarization of alerts, cases, or documents
Knowledge Graph & Relationship‑Based Analytics
- Ability to design and govern an enterprise knowledge layer defining relationship taxonomies, entity resolution rules, and linkage logic
- Ability to translate use cases into relationship‑driven analytical designs, such as Network‑based risk identification, Hidden association and indirect exposure analysis, Related‑party and concentric risk detection
Requirements
Data Platforms & Architecture
- Open table formats: Apache Iceberg, Delta Lake, Apache Hudi
- Distributed processing & query engines: Spark, Trino/Presto, Hive
- Cost optimization strategies: tiered storage, lifecycle management, workload governance
Programming & Analytics
- SQL, BTEQ, GCFR
- Python (Pandas, NumPy)
- BI & visualization tools: Power BI, QlikSense
Data Integration & Quality
- Informatica suite: PowerCenter, BDM, IDQ, Enterprise Data Catalogue
- Data ingestion patterns: batch, CDC, streaming
- Data validation, quality controls, and reconciliation frameworks within environments
Governance, Risk & Compliance
- Data modelling, critical data elements, regulatory reporting
- Fine-grained data access controls (row-level, column-level, masking)
- Metadata management, lineage, and impact analysis
- Compliance with BCBS 239, MAS, AML/CFT, and internal data standards
Big Data Platforms
- Cloudera Hadoop distribution: Hive, Impala, Spark, Iceberg, Trino
At least two relevant technical certifications across data platforms, cloud, or analytics technologies.
