“Techno-Functional” Analyst– Capital Markets Data Transformation

Role Description

The Techno-Functional Business Analyst will support a data transformation and controls remediation programme for a top-tier banking client, aligned to an ECB Remediation approach.

The role will support remediation governance, data quality gap assessment, controls automation, lineage and traceability, UAT, and audit-ready evidence production across business and technology stakeholders. The candidate will help ensure that remediation activities are clearly defined, prioritised, delivered, evidenced, and aligned to the required control and governance standards.

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.

Experience Requirements & Qualifications

• Minimum 5 years of relevant experience in data analytics, data quality, reporting controls, or data transformation programmes, preferably within financial services or Capital Markets.
• Experience working in regulated remediation environments, including exposure to audit evidence, controls testing, issue closure, and structured governance.
• Strong understanding of Capital Markets data, reporting expectations, and front-to-back data flows.
• Advanced SQL skills, including complex querying, performance tuning, reconciliation logic, and data validation.
• Strong Python skills for data analysis and automation, including pandas, validation frameworks, and scripting.
• Experience supporting or validating ETL/ELT pipelines and data quality frameworks, including rules, thresholds, exception handling, and control checks.
• Working knowledge of scheduling and orchestration tools such as Autosys and/or Apache Airflow, including schedule monitoring, reruns, and failure triage.
• Experience with CI/CD and release controls, including tools such as Git, Harness, UrbanCode Deploy, Red Hat OpenShift, or equivalent platforms.
• Familiarity with large-scale storage patterns such as AWS S3 for dataset movement, storage, and control validation.
• Experience supporting BI and reporting outputs such as Tableau dashboards, including data validation, extract refresh checks, and reconciliation to source systems.
• Strong documentation skills, with the ability to produce clear requirements, test evidence, control evidence, decision logs, and audit-ready materials.
• Strong stakeholder management skills, with the ability to coordinate across business, technology, risk, controls, and audit teams.

Nice-to-Have

• Experience with tools and technologies such as PySpark, Spark SQL, Hive, Impala, HDFS, Parquet, and Oracle databases.
• Exposure to data governance concepts including critical data elements, lineage, data quality dimensions, ownership, and audit frameworks.
• Experience supporting delivery activities such as intake, triage, prioritisation, wave planning, pod execution, and status reporting.
• Experience working in Agile or Scrum delivery models.
• Knowledge of monitoring and alerting tools for data pipelines, batch operations, and production controls.
• Familiarity with control frameworks, data controls, attestations, audit readiness, and issue management tooling such as DCRM.
• Familiarity with Visio or equivalent tools for process mapping, lineage mapping, and control documentation.

Main Tasks and Responsibilities

• Support the stand-up and operation of the remediation delivery model, including pod structure, intake process, tooling usage, delivery routines, and governance rhythms.
• Conduct discovery sessions with business, technology, controls, and reporting stakeholders to understand reporting objectives, key datasets, control expectations, and remediation edge cases.
• Drive quick-win remediation waves by supporting requirements definition, triage, prioritisation, stakeholder alignment, closure tracking, and evidence capture.
• Perform data profiling and produce findings on completeness, accuracy, consistency, and timeliness to support controls gap assessments and remediation planning.
• Design and execute reconciliation checks, including source-to-target, pre- and post-transformation, and report-to-underlying-data validations.
• Support the delivery and maintenance of controls gap assessment outputs, ensuring prioritisation, ownership, closure plans, and progress tracking are clearly documented.
• Identify data sourcing gaps, coordinate root-cause analysis with subject matter experts, and document agreed remediation and closure plans.
• Support manual controls automation waves by defining requirements, validating outputs, supporting testing, capturing evidence, and ensuring operational readiness.
• Ensure catalogue lineage is populated and that traceability coverage is measurable across critical data elements, transformation logic, reporting outputs, and key reporting chains.
• Lead or support UAT activities for reporting and controls, including test preparation, execution support, outcome validation, defect tracking, and sign-off evidence.
• Produce audit-ready documentation packs, including test packs, control evidence, lineage evidence, decision logs, reconciliation results, and explainable remediation outcomes.
• Track and communicate risks, issues, dependencies, decisions, and changes that may impact remediation outcomes, ensuring appropriate escalation and governance readiness.
• Ensure end-to-end traceability from requirement to transformation logic, quality checks, reporting outputs, control evidence, and audit artefacts.