Technical Analyst – Data Governance, Controls & Traceability

Boundaryless; Greater London; On-site; GBP 50,000 - 70,000; Full time

Job summary

Boundaryless is seeking a Business Analyst / Project Manager to support a crucial transformation program for a top-tier banking client based in Canary Wharf, London. The role entails extensive on-site collaboration, requiring a minimum of three days presence each week.

The ideal candidate will possess at least three years of relevant experience in data governance, compliance, and automation, coupled with proficiency in Python and SQL. You will be integral to the project, managing delivery routines while maintaining regulatory compliance.

Qualifications

• Minimum 3 years of experience in data governance, compliance, remediation, or automation programs.
• Proficient in Python, with experience in PySpark and Spark SQL.
• Hands-on experience designing ETL/ELT pipelines and data quality frameworks.

Responsibilities

• Support remediation stand-up and define tooling and delivery routines.
• Conduct discovery workshops to scope policies and control expectations.
• Produce control specifications and maintain remediation backlogs.

Skills

Data governance

Python

SQL

ETL/ELT pipelines

Data quality frameworks

Tools

PySpark

Spark SQL

AWS S3

Tableau

Oracle databases

Apache Airflow

Job description

Role Description

• The Business Analyst / Project Manager will support a transformation program for a top-tier banking client, aligned to an ECB Remediation approach.
• The Technical Analyst will support a Data Governance & Controls remediation program for a top-tier banking client, aligned to an ECB Remediation operating model.
• Support remediation stand-up and ways of working (pods, intake, tooling), helping establish delivery routines, governance, and reporting.
• Responsible for translating regulatory and governance policies (GDPR, CCPA, HIPAA, Basel, internal security standards) into clear technical requirements and control specifications.
• Work with Legal, Compliance, Security, Data Platform, and IT teams to define control requirements, maintain remediation backlogs, and track closure.
• Contribute to and maintain the controls gap assessment, including prioritization, ownership tracking, and closure evidence.
• Identify data sourcing gaps, coordinate root‑cause analysis with SMEs, and document and track the agreed closure plan.
• Support delivery of manual controls automation waves, ensuring requirements, testing, sign‑offs, and operational readiness are complete.
• Ensure catalogue lineage is populated and traceability coverage is measurable and reported for priority data domains and reporting chains.
• Engage in process mapping, control specification (decision tables, data contracts, rules), and validating outcomes through UAT and audit documentation.
• Participate from discovery workshops through implementation and continuous improvement.
• Ensure traceability from policy - control - implementation - test evidence - audit‑ready documentation pack.

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.

Core Skills & Experience

• Minimum 3 years of relevant experience in data governance, compliance, controls, remediation, or automation programs (preferably in financial services).
• Strong proficiency in Python for data engineering and automation.
• Hands‑on experience with PySpark and Spark SQL in production environments.
• Solid knowledge of Hive, Impala, HDFS, and Parquet.
• Advanced SQL skills; experience with Oracle databases.
• Experience designing and supporting ETL/ELT pipelines and data quality frameworks (rules, thresholds, exception handling).
• Working knowledge of Autosys and 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 AWS S3 for large‑scale data storage and dataset movement patterns.
• Experience supporting Tableau dashboards (data validation, extract refresh checks, reconciliation to source).

Nice‑to‑Have

• Experience in regulated or enterprise data environments (banking, compliance).
• Exposure to data governance, lineage, controls frameworks, and audit evidence standards.
• Experience working in factory‑style remediation models (intake, triage, prioritization, wave planning, pod execution, reporting).
• Experience working in Agile/Scrum delivery models.
• Knowledge of monitoring and alerting tools for data pipelines and batch operations.

Main tasks and responsibilities

• Support remediation stand‑up: pods structure, intake process, tooling setup, and delivery routines.
• Support remediation stand‑up: pods model, intake process, tooling usage, and delivery routines.
• Conduct discovery workshops to define scope, policies, control expectations, and remediation edge cases.
• Drive delivery of quick‑win remediation waves, including triage, tracking, and closure evidence capture.
• Produce control specifications and delivery artefacts (decision tables, data contracts, user stories, acceptance criteria, test cases).
• Maintain remediation backlogs (policy/control requirements) and track lifecycle changes, ownership, and closures.
• Support delivery and reporting of the controls gap assessment (prioritization, dependencies, closure tracking).
• Identify data sourcing gaps, coordinate SME working sessions, and document and track agreed closure plans.
• Support manual controls automation waves by validating requirements, coordinating testing, and ensuring sign‑off readiness.
• Ensure catalogue lineage is populated and traceability coverage is measurable and reported.
• Lead/support UAT for codified controls; validate automation outcomes and manage defect triage.
• Produce an audit‑ready documentation pack including decision logs, test packs, control mappings, lineage/traceability evidence, and approvals.
• Partner with developers to ensure policy intent is preserved in implementation and outcomes are explainable.