Technical Banking Analyst

Boundaryless Automation; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Boundaryless Automation is seeking an Agentic Technical/Business Analyst to support a Data Governance & Controls program for a top-tier banking client in London. The role requires translating regulatory policies into actionable development requirements and working with Legal, Compliance, Security, Data Platform, and IT teams.

You will map processes, define policy-as-code specifications, maintain the governance backlog, and drive UAT and audit documentation from discovery through implementation,

Qualifications

• Minimum 3 years in data governance, compliance, or automation programs.
• Strong Python proficiency for data engineering and automation.
• Hands-on PySpark and Spark SQL in production.
• Knowledge of Hive, Impala, HDFS, and Parquet.
• Advanced SQL skills; experience with Oracle databases.
• Experience designing ETL/ELT pipelines and data quality frameworks.
• Working knowledge of CI/CD tools and workflows.
• Experience with AWS S3 and data visualization (Tableau).

Responsibilities

• Conduct discovery workshops to define scope, policies, and edge cases.
• Produce control specifications (decision tables, user stories, test cases).
• Maintain the policy-as-code backlog and track lifecycle changes.
• Lead UAT for codified controls; validate automation outcomes.
• Document explainable outcomes and provide audit-ready evidence.
• Partner with developers to ensure policy intent is preserved in implementation.

Skills

Python for data engineering

PySpark

Spark SQL

SQL (Advanced)

Data governance / compliance

ETL/ELT design

UAT & audit

Policy-to-code understanding

Agile/Scrum

Data quality frameworks

Tools

Airflow

Autosys

Git

Harness

UrbanCode Deploy

OpenShift

AWS S3

Tableau

Job description

Role Description

• The Agentic Technical/Business Analyst will support a Data Governance & Controls program for a top-tier banking client.
• Responsible for translating regulatory and governance policies (GDPR, CCPA, HIPAA, Basel, internal security standards) into clear development requirements.
• Work with Legal, Compliance, Security, Data Platform, and IT teams to define policy-as-code specifications and maintain the governance backlog.
• Engage in process mapping, control specification (decision tables, data contracts, rules), and validating codified outcomes through UAT and audit documentation.
• Actively participate from discovery workshops through to implementation and continuous improvement.
• Ensure traceability from policy → control → audit evidence.

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 we do NOT offer visa sponsorship.

Experience Requirements & Qualifications

• Minimum 3 years of relevant experience in data governance, compliance, or automation programs.
• 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.
• Working knowledge of Autosys & Apache Airflow.
• Experience with CI/CD tools (Git, Harness, UrbanCode Deploy (UCD), Red Hat OpenShift).
• Familiarity with AWS S3 for large-scale data storage.Experience supporting Tableau dashboards.

Nice-to-Have

• Experience in regulated or enterprise data environments (banking, compliance).
• Exposure to data governance, lineage, and audit frameworks.
• Experience working in Agile/Scrum delivery models.
• Knowledge of monitoring and alerting tools for data pipelines.

Main Tasks and Responsibilities

• Conduct discovery workshops to define scope, policies, and edge cases.
• Produce control specifications (decision tables, user stories, test cases).
• Maintain the policy-as-code backlog and track lifecycle changes.
• Lead UAT for codified controls; validate automation outcomes.
• Document explainable outcomes and provide audit-ready evidence.
• Partner with developers to ensure policy intent is preserved in implementation.