At a Glance
- Tasks: Transform business questions into impactful data products and Power BI dashboards.
- Company: Join a fast-growing fintech improving financial wellbeing for millions.
- Benefits: Enjoy 25 days holiday, hybrid working, and generous perks.
- Other info: Collaborative team culture with excellent career growth opportunities.
- Why this job: Make a real difference in people's lives while developing your data skills.
- Qualifications: 3+ years in data analytics, SQL mastery, and Power BI expertise required.
The predicted salary is between 31500 - 38500 £ per year.
Working with employers, we provide a financial wellbeing platform as an employee benefit, helping employees to understand their money better, get out of debt faster and save for their future. We already have a reach of over 4,000,000 employees through our relationships with over 600 of the biggest companies in the UK. By improving employee financial wellbeing, we have a very real and meaningful impact on people’s lives. We remove the stress and worry associated with financial difficulties by dramatically reducing the interest rates employees pay on their personal debt, and provide them with the tools needed to start saving sooner and be more financially secure.
Your role in our mission
We are looking for a talented Enterprise Data Analyst to join our Enterprise Data Hub. Reporting to the Lead Enterprise Data Analyst, you will help translate business questions into trusted data products and Power BI dashboards, supporting Salary Finance's mission to help our customers get out of debt faster and save for their future. You'll work alongside senior analysts, engineers and stakeholders across the business building the datasets, reports, and insights that inform decisions and enable safe growth of our loan book. This is a role where you'll grow your craft, contribute to team standards, and see the impact of your work reach real customers.
What you’ll do
- You will liaise with stakeholders of all data literacy levels to develop robust dashboard requirements.
- You will build, design, develop and maintain best-in-class Power BI dashboards which serve a purpose and deliver value to the business.
- You will help the automation of manual reporting processes and end-to-end operational workflows, ensuring high uptime and seamless maintenance of production reports.
- You will regularly audit existing report performance and SQL scripts to reduce technical debt and improve processing speeds as data demand scales.
- You will follow the team's data governance standards and contribute to documentation across your analytical outputs.
- You will build optimised scalable data products and robust data marts, creating a structured environment for self-service analytics.
- You will collaborate with Enterprise Data Engineers to refine ETL/ELT pipelines, ensuring the upstream data architecture supports downstream analytical requirements.
About you
- Proven Track Record: At least 3+ years of experience in data analytics, business intelligence, or similar roles, with a demonstrable history of progressing from technical execution to strategic delivery.
- SQL Mastery: Advance level proficiency in writing, optimising, and debugging complex queries. You should be comfortable handling large-scale datasets and understanding relational database architecture.
- Power BI & DAX Specialist: Advanced command of the Power BI ecosystem. You don't just build reports; you create sophisticated DAX measures and perform complex data modeling to solve intricate business logic.
- Strategic Stakeholder Management: A proven ability to act as a bridge between technical data and business needs. You can translate "vague requests" into concrete technical requirements and present findings to executives with confidence.
- Insight Delivery & Storytelling: You possess a "so what?" mindset. You have a track record of moving beyond descriptive reporting to deliver predictive insights that drive measurable commercial value.
- LLM Literate: You are comfortable using LLMs (e.g., Claude, Gemini) to accelerate your workflow, whether for logic verification, documentation, or streamlining code development.
Nice to have:
- Experience in financial services or a similar regulated industry (e.g., FinTech, banking).
- Prompt Engineering for Data: You are well-versed in prompt engineering techniques to optimise data cleaning, generate SQL scripts, or automate metadata documentation.
- Python for Analytics: Ability to use Python for data manipulation (Pandas/NumPy), automation scripts, or basic statistical modeling to augment standard BI toolsets.
- Data Governance Frameworks: Practical experience establishing data dictionaries, lineage, and quality protocols to ensure a "single source of truth."
- Forecasting & Predictive Modeling: Experience building time-series forecasts or predictive models to help the business anticipate trends, demand, or churn.
- Technical Mentorship: Experience in peer-reviewing code (SQL/DAX) and coaching junior analysts to uphold high standards of accuracy, performance, and design.
Who you are
- Take Ownership: We own the entire journey and see outcomes through from start to finish.
- Dig Deeper: We ask why, investigate root causes, and build solutions that last.
- Stronger Together: We choose collaboration, share knowledge freely, and lift each other up.
- Momentum Matters: We act with purpose, remove blockers, and default to action.
- Make a Lasting Impact: We think long-term, put people before numbers, and change the system for good.
What do you get for all your hard work?
- 25 days holiday with an additional day off for every year of service up to 30 days and an extra day off on your birthday.
- Hybrid working arrangements so you can work from the office and from home with a budget to help you get set up.
- Generous company benefits to include pension and life assurance and an annual allowance to spend on medical insurance, health cash plan, denplan, gym memberships.
- Enhanced policies that are family and pet friendly, to include company sick pay and peternity leave.
- Great career development in a fast paced environment.
- Volunteer days as part of our CSR program.
- Regular company socials & more great perks to include weekly snacks, tuckshop, cycle to work, help to save and much more!
The typical interview process
- Introductory call with our Talent Manager (phone call - 20 mins).
- 1st Stage: Technical interview (PowerBI exercise) with Hiring Manager and team (video call - 60 mins).
- 2nd Stage: Past work experience and culture interview with Hiring Manager and team (in person - 60 mins).
We’re looking for people that will get stuck in and make a difference. We have a great collaborative, entrepreneurial team and are passionate about what we do. If you want to join a team that is changing people’s lives for the better then we’d love to hear from you.
Salary Finance is proud to be an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive work environment where all employees and applicants can flourish. If there’s anything we can do to accommodate your specific situation, please let us know.
Enterprise Data Analyst employer: Salary Finance
Salary Finance is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong focus on employee growth, we offer continuous learning opportunities and the chance to make a meaningful impact through data-driven decision-making. Our hybrid work model ensures flexibility while being part of a dynamic team dedicated to enabling safe growth in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Enterprise Data Analyst
✨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 Salary Finance!
✨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 Enterprise Data Analyst at Salary Finance.
✨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 Salary Finance.
✨Apply Directly through Our Website
When you find a suitable opening like Enterprise Data Analyst at Salary Finance, 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 Enterprise Data Analyst
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 Salary Finance, 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 Salary Finance. 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 Salary Finance
✨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 Salary Finance!
✨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.
