At a Glance
- Tasks: Lead data delivery projects and collaborate with teams to drive analytics and AI integration.
- Company: Join QBE, a forward-thinking company focused on data-driven decision-making.
- Benefits: Enjoy 30 days holiday, flexible working options, and a generous pension plan.
- Other info: Great opportunities for career growth and development in a dynamic environment.
- Why this job: Make a real impact by embedding data and analytics into business strategies.
- Qualifications: Experience in data delivery and strong stakeholder engagement skills required.
The predicted salary is between 60000 - 75000 £ per year.
Location: London
Type: Permanent, full time
Flexible working: Happy to talk flexible working
The Opportunity
QBE Europe is recruiting a Data Delivery Manager to join the EO Data & Analytics function and partner with a defined business value stream. As part of QBE EO’s transformation journey, this role helps embed data, analytics and AI into day‑to‑day decision‑making, operational performance and regulatory outcomes. The Data Delivery Manager is accountable for turning agreed value stream priorities into a clear, governed data delivery roadmap, and for maintaining oversight of progress, risks and dependencies through to delivery and adoption. Working closely with business stakeholders and Data & Analytics delivery teams, the role ensures delivery is aligned to strategy, follows appropriate governance, and demonstrates measurable value. Having the right to work in the UK is a requirement for this role. QBE may consider sponsorship at its discretion.
Your New Role
- Act as the primary data & analytics partner for an assigned business value stream, maintaining strong stakeholder relationships and a clear understanding of priorities, demand and current challenges.
- Own the intake and shaping process for data and analytics demand in line with defined business objectives and priorities.
- Manage and prioritise the data delivery backlog across Run and Change, ensuring solutions and processes are robust, scalable and sustainable; maintain a clear view of capacity, sequencing, dependencies and trade‑offs.
- Ensure the value stream follows agreed Data & Analytics delivery standards, templates and ways of working (including analysis and BI deliverables), and improve these where appropriate.
- Work with data quality analysts and domain SMEs to identify material data issues impacting the value stream, prioritise remediation items, and escalatory risks where required.
- Lead a team of analysts and data professionals within the value stream by setting clear objectives, allocating work, and ensuring high‑quality outcomes.
- Coach and develop team members through regular 1:1s, mentoring and performance feedback, supporting capability growth and career progression.
- Ensure delivery activities align with audit, risk and control requirements, maintaining appropriate documentation and escalating issues in line with governance.
- Define, track and report success metrics to demonstrate the business value delivered by data products and initiatives.
- Provide regular updates on progress, risks, issues and dependencies, proposing options and actions where trade‑offs are required.
- Support resource planning with other Data Delivery Managers and the Data Strategy & Operations Manager, helping manage capacity constraints across value streams.
- Support the adoption of delivered analytics, insights and AI solutions within your value stream by working closely with Business Change Managers and Data Adoption Lead.
- Maintain a working understanding of QBE’s AI governance policies and processes and support the value stream to operate in line with them.
- Maintain visibility of AI and advanced analytics use cases within the value stream, (planned and delivered), including documentation status, controls and value being realised.
- Support business stakeholders to understand AI governance requirements (e.g., controls, audit expectations and responsible use), escalating material risks or gaps where required.
About You
- Experience supporting the delivery of data, analytics or technology initiatives within a complex organisation.
- Experience leading or supervising analysts or delivery team members, with a focus on coaching and capability development.
- The ability to translate business needs into clear and actionable data and analytics requirements.
- Experience working in agile, product or value‑stream‑based delivery environments.
- Strong stakeholder engagement skills, with the confidence to work with a range of business and technical partners.
- A solid understanding of data, analytics and AI concepts, including basic governance and risk considerations.
- Clear communication skills, with the ability to explain delivery progress and outcomes to both technical and non‑technical audiences.
Skills & Experience Desirable
- Experience working within financial services or regulated environments.
- Exposure to data governance, data quality, lineage or metadata management practices.
- Experience supporting analytics or reporting platforms (e.g. BI tools, data warehouses, cloud data platforms).
- Familiarity with tracking benefits realisation and delivery success metrics.
- Experience working across multiple delivery teams or value streams simultaneously.
- Experience supporting learning and development plans or career progression for analysts.
- An interest in emerging analytics and AI capabilities and their responsible application in a business context.
Benefits
- 30 days holiday a year with the option to buy up to 2 additional days.
- Flexible working – balancing work and life is important so our flexible working opportunities are open to all, including part‑time, job share and compressed hours.
- Pension – you are automatically enrolled into the QBE pension plan, which entitles you to receive employer contributions of 10% of your basic salary.
Application Close Date: 29/05/2026 11:59 PM
Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.
Data Delivery Manager employer: hackajob
QBE Europe is an exceptional employer, offering a dynamic work environment in London where flexibility and work-life balance are prioritised. With a strong focus on employee growth, the company provides ample opportunities for professional development through coaching and mentoring, alongside competitive benefits such as 30 days of holiday and a generous pension plan. Join us to be part of a transformative journey that integrates data, analytics, and AI into meaningful business outcomes while fostering a culture of collaboration and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Delivery Manager
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like hackajob!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Delivery Manager at hackajob.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hackajob.
✨Apply Directly through Our Website
When you find a suitable opening like Data Delivery Manager at hackajob, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Delivery Manager
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at hackajob, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hackajob. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at hackajob
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hackajob!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.