At a Glance
- Tasks: Support data quality and governance in a dynamic banking environment.
- Company: Join a top-tier banking client in the heart of London.
- Benefits: Permanent position with competitive salary and career growth opportunities.
- Other info: Collaborative team culture with a focus on innovation and excellence.
- Why this job: Make a real impact on data governance and regulatory compliance.
- Qualifications: 5+ years in data governance, strong SQL and Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
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)
- 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).
- Support validation readiness by producing clear, audit-ready documentation and evidence packs.
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 → CDE → SOR/AR → controls → lineage → exception management → 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 we do NOT offer visa sponsorship.
Core Experience
Experience Requirements & Qualifications
- 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.
Banking Data Quality Analyst employer: Boundaryless Automation
As a leading employer in the financial services sector, we offer a dynamic work environment in Canary Wharf, London, where innovation and collaboration thrive. Our commitment to employee growth is evident through continuous training opportunities and a culture that values diversity and inclusion. Join us to be part of a team that not only drives data governance excellence but also fosters meaningful career development in a top-tier banking context.
StudySmarter Expert Advice🤫
We think this is how you could land Banking Data Quality Analyst
✨Tap into Campus Networks
If you're still in uni, don’t forget to engage with your campus's career services and attend finance-related events. Banks often do presentations and recruitment drives on campus, so put yourself out there and make use of these opportunities to show off your passion for the field.
✨Get Certified
Consider pursuing relevant certifications like the CFA or ACCA while you’re job hunting. They not only beef up your CV but also connect you with professional bodies which can lead to networking opportunities and even job openings in banking and financial services.
✨Connect on Professional Platforms
Join finance-focused groups on platforms like LinkedIn and engage in discussions. This can really help you stand out from the crowd, allowing potential employers to see your knowledge and interest in industry trends. Plus, you might stumble upon job postings shared exclusively within the group.
✨Apply Directly and Be Proactive
Don’t shy away from reaching out directly to firms like Boundaryless Automation. Use their websites and apply through them, but also consider following up with a polite email to express your enthusiasm. Being proactive can make a huge difference in getting noticed in the competitive financial services sector.
We think you need these skills to ace Banking Data Quality Analyst
Some tips for your application 🫡
Show Off Your Numbers!:In the banking and financial services world, quantifiable achievements are key. Make sure your CV highlights your grades in relevant subjects, any financial certifications you hold, and specific projects where you've delivered measurable results. Employers love to see how your skills translate into real-world success.
Tailor Your Cover Letter to the Role:When applying for a full-time position, your cover letter should make a direct connection between your experience and the job description. Don't just state your enthusiasm for finance—dive into how your background in banking or financial analysis sets you apart. Let your passion shine through while being specific about what you can bring to Boundaryless Automation.
Include Relevant Financial Software Experience:If you've worked with financial modelling tools or software like Excel, SAP, or specific analytical tools during your studies or internships, bring that up! Highlighting your proficiency can really make your application pop and show you're ready to hit the ground running in a full-time role.
Research and Reflect:Before hitting that 'apply' button on Boundaryless Automation's website, do a little digging. Look up their recent projects, values, and culture. Reflecting their ethos in your application can make a huge difference and show you’re genuinely interested in being part of the team!
How to prepare for a job interview at Boundaryless Automation
✨Brush Up on Financial Analysis Skills
Make sure you're well-versed in financial concepts and analytical techniques relevant to banking and financial services. Get comfortable with tools like Excel for modelling or financial forecasting, as technical questions in this area are common during interviews with Boundaryless Automation.
✨Prepare for Case Studies
Expect to tackle case studies that demonstrate your problem-solving skills in real-world banking scenarios. Familiarise yourself with the types of problems you might face—think risk assessments or investment evaluations—and be ready to articulate your thought process clearly.
✨Show Your Passion for Finance
Since this is a full-time position, employers at Boundaryless Automation will be keen to see your genuine interest in finance. Be prepared to discuss recent industry trends or news articles that excite you, showcasing your enthusiasm and engagement with the field.
✨Network with Industry Professionals
Before your interview, reach out to current or former Boundaryless Automation employees on platforms like LinkedIn. They'll offer unique insights into the company's culture and the interview process, which can give us a delightful edge in showcasing a good fit for the team.
