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- Tasks: Lead data governance practices in Agile teams within the banking sector.
- Company: Join a leading financial institution focused on innovation and compliance.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a significant impact on data governance in a dynamic banking environment.
- Qualifications: Expertise in data architecture, governance, and compliance required.
- Other info: Collaborative culture with a focus on continuous improvement and audit readiness.
The predicted salary is between 60000 - 84000 £ per year.
The Data Domain Governance Lead is responsible for embedding robust data governance practices across Agile delivery teams within the banking domain. Operating within a SAFe Agile framework, this role ensures that data standards, models, lineage, privacy, and controls are consistently applied across delivery pipelines. The successful candidate will bring deep expertise in data architecture, metadata management, privacy compliance, and data quality, enabling scalable and audit-ready data ecosystems.
Responsibilities
- Portfolio & Program Alignment: Ensure governance guardrails are considered during PI Planning and reflected in Agile Features.
- System Architecture & SME Support: Act as a System Architect and Shared Services SME to support Agile Release Trains (ARTs) in embedding governance principles.
- Guidance to Agile Teams: Provide expert guidance to Agile Teams on integrating data governance into delivery workflows and feature design.
- Canonical Data Models & Standards: Collaborate with Business and Source of Record (SOR) stakeholders to define and maintain domain-level canonical (conceptual) data models.
- Metadata & Lineage: Review metadata/catalogue entries to ensure critical datasets have clear ownership, lineage, and business semantics.
- Data Modelling Practices: Support Agile Teams in applying consistent data modelling practices and semantic layer alignment.
- Data Quality & Controls: Translate EDM policies into domain-specific rules and acceptance criteria; partner with delivery teams to embed automated data quality checks and validation rules into data pipelines; ensure Features include required data quality controls and contribute to Definition of Done and acceptance criteria.
- Metadata, Lineage & Privacy Governance: Guide Agile Teams in embedding lineage capture and metadata tagging within delivery pipelines using modern tooling (e.g., Collibra, Informatica, Alation); ensure consistent application of metadata standards and lineage tracking across domains.
- Privacy & Retention: Oversee PII and sensitive data classification, labelling, and handling in accordance with data privacy regulations; define and enforce archival and retention policies for domain data assets, ensuring compliance and operational efficiency.
- Audit Insights & Continuous Improvement: Analyse audit findings and feedback to identify gaps and improvement opportunities in data governance practices; strengthen domain-level data controls and quality frameworks based on audit insights.
Required Skills & Experience
- Strong understanding of Treasury and/or Corporate Banking domains, including products, processes, and regulatory requirements.
- Advanced data modelling expertise, including designing conceptual, logical, and physical models for complex financial domains; applying semantic modelling for BI and analytics; knowledge of normalization, denormalization, and performance optimization; hands-on experience with modelling tools such as ERwin, PowerDesigner, or equivalent.
- Strong background in enterprise data architecture.
- Hands-on experience with metadata and lineage tools such as Collibra, Informatica Enterprise Data Catalog, Alation, Microsoft Purview.
- Deep understanding of data privacy regulations and compliance standards and local banking regulations.
- Experience implementing PII classification, data sensitivity labelling, and access controls using tools.
- Knowledge of data archival and retention policies relevant to financial records and audit trails.
- Experience defining and implementing automated data quality rules and controls for datasets.
Preferred Qualifications
- Experience implementing industry-standard data governance frameworks such as DAMA-DMBOK, DCAM, and COBIT.
- Experience in large-scale financial institutions or treasury functions.
- Knowledge of data vault modelling and graph modelling for advanced use cases.
- Familiarity with data observability tools and practices to monitor data health, lineage, and reliability across pipelines.
Data Domain Governance Lead in City of London employer: Ascendion
Contact Detail:
Ascendion Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Domain Governance Lead in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the banking and data governance space on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Prepare for those interviews by brushing up on your knowledge of data governance frameworks like DAMA-DMBOK and COBIT. Be ready to discuss how you’ve applied these in real-world scenarios. We want to see your expertise shine!
✨Tip Number 3
Showcase your hands-on experience with tools like Collibra and Informatica during interviews. Bring examples of how you’ve used these tools to improve data quality or compliance. This will set you apart from the competition!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Domain Governance Lead in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Domain Governance Lead role. Highlight your experience in data governance, Agile methodologies, and any relevant banking domain knowledge. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data governance and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality come through!
Showcase Relevant Projects: If you've worked on projects that involved data architecture, metadata management, or compliance, make sure to mention them. We’re keen to see real examples of your work and how you've applied your skills in practical situations.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about StudySmarter and what we stand for!
How to prepare for a job interview at Ascendion
✨Know Your Data Governance Inside Out
Make sure you brush up on your knowledge of data governance practices, especially within the banking domain. Be ready to discuss how you've applied these principles in past roles and how they can be integrated into Agile workflows.
✨Familiarise Yourself with SAFe Agile Framework
Since this role operates within a SAFe Agile framework, it’s crucial to understand its principles. Prepare examples of how you've successfully worked in Agile environments and how you can support Agile Release Trains in embedding governance.
✨Showcase Your Technical Skills
Be prepared to talk about your hands-on experience with data modelling tools like ERwin or PowerDesigner, as well as metadata and lineage tools such as Collibra or Informatica. Highlight specific projects where you’ve used these tools to improve data quality and compliance.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in data governance. Think of situations where you identified gaps in data practices and how you implemented solutions. This will demonstrate your analytical thinking and ability to drive continuous improvement.
