Senior Business Data Analyst - M&G plc.

Senior Business Data Analyst - M&G plc.

Full-Time 57036 - 69710 £ / year (est.) Home office (partial)
eFinancialCareers

At a Glance

  • Tasks: Lead complex data analysis and bridge business needs with technology delivery.
  • Company: M&G plc, a historic leader in savings and investments.
  • Benefits: Flexible working arrangements, workplace adjustments, and a focus on wellbeing.
  • Other info: Join a dynamic team with opportunities for professional growth in financial services.
  • Why this job: Make a real impact by shaping sustainable data outcomes in a collaborative environment.
  • Qualifications: Expertise in business and data analysis, with strong SQL skills.

The predicted salary is between 57036 - 69710 £ per year.

At M&G, our purpose is to give everyone real confidence to put their money to work.

With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions.

Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions.

Through telling it like it is, owning it now and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent.

We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role.

This senior role supports data delivery and transformation activity across business and technology teams.

The role acts as a bridge between business needs and technology delivery, combining business analysis, data analysis and hands‑on source‑system investigation to shape practical, traceable and sustainable data outcomes.

The role holder will lead complex data analysis, challenge requirements constructively and help stakeholders align on data definitions, priorities and strategic data initiatives.

They will work closely with business SMEs, Product Owners, Data Owners, data engineering teams and senior stakeholders to make sure requirements are clear, validated and ready to build.

This role is well suited to someone who can bring structure to complex data problems, communicate clearly across technical and non‑technical audiences, and use judgement to balance business value, delivery constraints, data quality, cost and risk.

  • Main Responsibilities
  • Lead the documentation and cataloguing of data requirements for existing and redesigned business processes.
  • Lead complex data analysis to validate business requirements, including direct investigation of source systems.
  • Translate data requirements into measurable business outcomes that support improved decision‑making and operational efficiency.
  • Assess and document upstream and downstream data flows, dependencies and interdependencies within the enterprise data architecture.
  • Produce clear technical change specifications, User Stories and narratives that technology teams can build against, with end‑to‑end traceability.
  • Interrogate and sense‑check requirements from a sustainable data perspective.
  • Challenge constructively and provide alternative options where requirements are unfeasible or technically costly.
  • Work closely with data engineering teams to make sure requirements are accurately converted into built data products.
  • Influence senior stakeholders to align on data definitions, priorities and strategic data initiatives.
  • Lead data quality assessments and support the development of data‑driven improvement strategies.
  • Apply data governance in line with enterprise data governance frameworks.
  • Build strong working relationships across business SMEs, data engineering teams and senior stakeholders.
  • Key Knowledge, Skills and Experience
  • Proven expertise combining business analysis, data analysis and data cataloguing.
  • Ability to identify, document and validate complex data requirements.
  • Ability to analyse source systems and data, validating information rather than relying only on stakeholder input.
  • Proven expertise in Agile methodologies, writing good user stories in agile teams including validated definition of done / acceptance criteria.
  • Proficient use of enterprise data platforms, semantic models and dimensional modelling.
  • Working knowledge of star schemas, fact tables and dimension tables.
  • Proficient understanding of data architecture principles, ETL processes and data pipeline concepts.
  • Track record of data modelling, data architecture and use of data cataloguing tools.
  • Proficiency in SQL for data validation and analysis.
  • Familiarity with data visualisation tools and cloud based data platforms.
  • Familiarity with Snowflake, Azure, Databricks and Power BI.
  • Track record of translating complex data requirements into technical specifications in financial services and/or Life operations.
  • Ability to translate technical data concepts into business friendly language for stakeholders up to senior leadership level.
  • Strong experience working in financial services, with exposure to the Life industry and a plc environment an advantage.
  • Suggested Essential Skills
  • Complex data requirements analysis
  • Source‑system investigation
  • Data quality assessment
  • Data governance application
  • Technical specification writing
  • End‑to‑end requirements traceability
  • Data modelling and data architecture
  • Data cataloguing
  • SQL for validation and analysis
  • Cloud based data platform awareness
  • Senior stakeholder engagement
  • Constructive challenge and influencing
  • Practical problem solving
  • Collaboration across business, data and technology teams

What we offer

We're dedicated to supporting your wellbeing and helping you thrive, both at work and beyon

#J-18808-Ljbffr

Senior Business Data Analyst - M&G plc. employer: eFinancialCareers

Quilter plc is an exceptional employer, offering a dynamic work environment in Southampton where innovation and collaboration thrive. With a strong commitment to employee growth, comprehensive benefits including a generous holiday allowance and a non-contributory pension scheme, Quilter fosters a culture of inclusivity and continuous improvement, empowering employees to make meaningful contributions to the financial futures of their clients and communities.

eFinancialCareers

Contact Details:

eFinancialCareers Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Business Data Analyst - M&G plc.

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 eFinancialCareers!

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 Senior Business Data Analyst - M&G plc. at eFinancialCareers.

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 eFinancialCareers.

Apply Directly through Our Website

When you find a suitable opening like Senior Business Data Analyst - M&G plc. at eFinancialCareers, 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 Senior Business Data Analyst - M&G plc.

Business Analysis
Data Analysis
Data Cataloguing
Source-System Investigation
Agile Methodologies
User Story Writing
Data Architecture Principles

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 eFinancialCareers, 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 eFinancialCareers. 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 eFinancialCareers

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 eFinancialCareers!

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.