Banking Data Quality Analyst

Role Description

• The Techno-Functional Business Analyst will support a banking Data Quality / Data Under Governance program aligned to the proven UK DQP approach (PRA) and now being replicated across ECB and India regulatory asks.
• Support delivery across the five workstreams:
• CDE Identification (CDE inventory, definitions, ownership, scope by legal entity)
• SOR Allocation (authoritative source mapping, SoR/AR alignment, data contracts)
• Controls Mapping (control design, thresholds, risk appetite alignment, evidence requirements)
• Data Lineage (traceability across systems, transformation chains, endpoints/reporting)
• Operating Model (DCRM workflow, exception management, governance routines, reporting)

Work with Markets, Risk, Finance, Operations, Technology, Data Platform, and Governance teams to drive outcomes and ensure regulatory alignment.

Translate regulatory expectations into clear requirements and executable delivery artefacts (user stories, decision tables, STTMs, test packs).

Ensure traceability from policy/regulatory expectation to CDE to SOR/AR to controls to lineage to exception management to audit evidence.

Support validation readiness by producing clear, audit-ready documentation and evidence packs.

Location

• The role supports one of our top-tier banking clients in London (Canary Wharf) and requires a minimum of three days on-site presence .
• This is a permanent position based in the UK . We will only consider applicants who are eligible to work in the UK. For this role do NOT offer visa sponsorship.

Experience Requirements & Qualifications

Core Experience

• Minimum 5 years of relevant experience in data governance, data quality, reporting controls, or data transformation programs (preferably in financial services / Capital Markets).
• Proven experience delivering governance-led programs involving CDEs, SOR/authoritative sources, controls, and lineage .
• Experience working in regulated remediation / regulatory delivery environments with exposure to validation, audit evidence, and structured governance.
• Strong stakeholder management across business, operations, technology, and governance functions.

Domain Knowledge

• Strong understanding of Capital Markets and Finance data domains (front-to-back awareness is a plus).
• Familiarity with risk appetite concepts as applied to data quality thresholds and control exceptions.

Technical / Analytical Skills

• Proficiency in SQL (advanced querying, reconciliation logic, data validation).
• Strong proficiency in Python for data analysis and automation (pandas, validation frameworks, scripting).
• Experience supporting or validating ETL/ELT pipelines and data quality frameworks (rules, thresholds, exception handling).
• Exposure to lineage and metadata approaches; ability to validate transformations and trace data across platforms.

Tooling / Delivery Methods

• Working knowledge of scheduling/orchestration tools such as Autosys and/or Apache Airflow (monitoring schedules, reruns, failure triage).
• Experience with CI/CD and release controls (Git, Harness, UrbanCode Deploy (UCD), Red Hat OpenShift or equivalent).
• Familiarity with large-scale storage patterns (e.g., AWS S3) for dataset movement and controls.
• Experience supporting BI/reporting outputs such as Tableau dashboards (data validation, extract refresh checks, reconciliation to source).

Nice-to-Have

• Experience with tools such as PySpark, Spark SQL, Hive, Impala, HDFS, Parquet, and Oracle databases.
• Hands-on exposure to DCRM tooling and operational exception management processes.
• Experience with governance/catalog tools and lineage documentation methods (Collibra/Alation/Informatica EDC/Purview or similar).
• Experience running delivery routines across workstreams (intake, triage, prioritization, wave planning, reporting).
• Experience working in Agile/Scrum delivery models.
• Familiarity with Visio (or equivalent) for lineage, control mapping, and operating model workflows.

Main tasks and responsibilities

• Run discovery workshops to confirm scope by legal entity, regulatory asks, priority datasets, and key stakeholders.
• Build and maintain CDE inventory : definitions, ownership, criticality, and mapping to reports/processes.
• Support SOR / Authoritative Source allocation : document authoritative sources, data contracts, and key dependencies.
• Define and maintain controls mapping : control points on SOR, AR, and endpoints; thresholds aligned to risk appetite; evidence requirements.
• Support data lineage creation/validation: source-to-endpoint traceability, transformation logic validation, and coverage reporting.
• Define and embed the operating model : exception workflows, DCRM lifecycle, triage routines, governance reporting, and closure evidence.
• Perform data profiling and reconciliation checks to support control design and validation readiness.
• Lead/support UAT and validation activities; coordinate defect triage and ensure sign-off evidence is complete.
• Produce an audit-ready documentation pack: lineage evidence, controls evidence, test packs, decision logs, and explainable outcomes.
• Track and communicate risks, dependencies, and changes impacting regulatory delivery outcomes through governance forums.

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