Assistant Vice President- Data Analyst

Key Responsibilities The Senior Analyst will be responsible for managing data and business requirements with multiple domains of core banking. Specific responsibilities include: 1. Subject Matter Expertise & Source System Analysis: Subject matter expert on the data str uctures and business processes of key financial product systems, including Trade Finance, Lending, Financial Markets/Treasury, and CASA/Core Banking.

Analyse the data models of these new source systems to understand table structures, key relationships, data fields, and their business meaning. Perform detailed data profiling and analysis to validate documentation against actual data, identifying data quality issues, gaps, and nuances at the source. 2. Data Modelling & Mapping: Collaborate closely with Data Architects and Engineers to define and refine the logical Domain Data Model within the Databricks Lakehouse (Silver Layer).

Lead workshops with business SMEs from Trade Finance, Lending, Treasury, and Operations to gather detailed data requirements for downstream consumers (e.g., regulatory reports, financial statements, risk dashboards). Create and own comprehensive, field-level Source-to-Target Mapping (STM) documents, detailing the precise transformation logic required to move data from source systems (Trade, Lending, etc.) to the curated Gold Layer of the data platform. 3. Stakeholder Collaboration & Functional Support: Serve as the Single Point of Contact (SPOC) for all functional data-related queries from internal teams and external vendors involved in the development and testing of ETL/ELT pipelines.

Provide expert data analysis support to business and operations teams, helping them understand data lineage, troubleshoot data discrepancies, and perform ad-hoc analysis to answer complex business questions. Work with the Data Governance specialist to document business definitions, data quality rules, and metadata for critical data elements within the enterprise data catalog. Actively participate in SIT (System Integration Testing) and UAT (User Acceptance Testing) to validate that data pipelines and reports meet the specified business requirements.

Key Deliverables Data Model Assessment : Comprehensive analysis of upstream system data models (Trade360, ACBS, Murex, Flexcube). Domain Data Model : Defined and documented domain data model in Databricks. Mapping Documentation : Field-level mappings and transformation rules for target systems.

Query Resolution : Timely resolution of functional data queries from vendors and stakeholders. Data Analysis : Insights and reports to support business and operations teams. Qualifications & Experience Required: Bachelor’s degree in Finance, Economics, Information Systems, or a related field. 9-12 years of experience as a Data Analyst, Business Analyst, or Systems Analyst within the Banking and Financial Services (BFS) domain.

Mandatory hands-on experience and functional understanding of the data models of at least two of the following core banking systems, Trade Finance: CGI Trade 360; Lending: ACBS; Treasury / Financial Markets: Murex; CASA/Deposits): Oracle Flexcube, or similar products. Proven experience in creating detailed Source-to-Target Mapping documents and functional specification documents. Strong proficiency in data management tools, SQL for complex data querying, analysis, and data profiling, visualization tools.

Desired/Preferred: Experience working on large-scale data migration, data warehousing, or core banking transformation projects. Familiarity with modern data platforms and concepts (e.g., Data Lakehouse, Medallion Architecture). Experience with Databricks or PySpark is a significant advantage.

Knowledge of financial and regulatory reporting requirements in the banking sector.