Job Summary
As part of the ROC Programme’s foundation-building phase, two experienced Data Analysts are required to support the development of a scalable and sustainable Semantic Phone Book. This asset will enable consistent interpretation of data across the Bank by bridging physical data structures with enterprise business semantics.
The analysts will conduct technical deep dives into source systems holding critical banking data. Their work will inform accurate, trustworthy mappings between raw data fields and defined business concepts forming a cornerstone for data transparency, self-service analytics, regulatory compliance, and future data platform modernisations.
Findings will feed directly into ROC Programme deliverables, including target-state data architectures, governance workflows, and cross-functional data harmonisation efforts.
Core Responsibilities
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Perform hands-on analysis of banking source systems, including databases, tables, ETL jobs, interface files, reports, extracts, and technical specifications.
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Extract and document metadata at scale: identifying entities, attributes, keys, relationships, data types, constraints, and usage contexts.
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Profile actual data populations using SQL to assess completeness, uniqueness, validity, consistency, format adherence, and value distributions.
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Develop comprehensive field-level catalogues and physical data dictionaries for assigned systems.
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Propose candidate semantic mappings between physical data elements and defined business attributes (e.g., “Client Tax Residence”, “Transaction Channel Type”) using standardised frameworks.
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Identify and log critical data issues such as:
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Redundant or duplicated structures
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Ambiguous column names or unclear ownership
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Inconsistent coding schemes (e.g., ‘Y’ vs ‘Yes’ vs ‘1’)
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Poor data quality indicators (high null rates, unexpected ranges)
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Maintain structured outputs in centrally managed templates and repositories under guidance from the Senior Semantic Mapping Lead.
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Contribute to source-to-target mapping documentation and preliminary data lineage diagrams.
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Prepare evidence-backed review packages for discussion with business SMEs, IT stewards, and migration squads.
Key Responsibilities
Required Qualifications and Experience
Mandatory Skills and Background
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Minimum 5 years' experience in technical data analysis, preferably within global financial institutions.
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Proven track record in source system analysis, including reverse-engineering data models from live environments.
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Advanced SQL proficiency: ability to write efficient queries for exploration, sampling, aggregation, and anomaly detection (across Oracle, MS SQL Server, DB2, etc.).
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Demonstrated involvement in semantic mapping initiatives or metadata management programmes.
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Sound grasp of data governance fundamentals, including metadata repositories, data dictionaries, and mapping inventories.
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Familiarity with common data formats and interfaces: CSV, XML, JSON, fixed-width files, API responses, report layouts.
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Strong documentation discipline and experience maintaining structured templates under tight timelines.
Domain Expertise
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Banking industry experience is mandatory, ideally covering one or more of the following areas:
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Client and account management
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Transaction processing and payment flows
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Product master data
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Fees, commissions, and revenue tracking
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Finance & regulatory reporting (e.g., AIFMD, FATCA, CRS)
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Core banking platforms (retail/private banking focus preferred)
Working Style and Behavioural Expectations
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Highly structured, fact-based, and evidence-driven in approach.
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Capable of investigating real systems and live data, not relying solely on outdated documentation.
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Able to manage large volumes of attributes and interdependent systems efficiently.
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Clear distinction between confirmed facts, plausible assumptions, candidate proposals, and open questions.
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Ability to escalate ambiguities proactively, particularly around meaning, ownership, or conflicting definitions.
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Commitment to consistency in documentation, alignment with taxonomy standards, and collaboration within the wider data community.