Senior Data Analyst
Job Title: Senior Data Analyst
Location: London, United Kingdom (4 days a week in the office)
This non for profit wihtin the financial services sector has been the UK’s leading affordable housing aggregator for more than three decades, providing innovative funding solutions for 149 housing associations across all four nations of the UK. They have amassed a near £8bn loan book to date and continues to expand its range of financial products to serve the needs of the social housing sector. My client has made significant contributions toward solving the UK’s affordable housing crisis, having funded 32,000+ homes under Affordable Housing Finance Plc (AHF), which oversaw the government’s initial Affordable Housing Guarantee Scheme. The aggregator launched Blend Funding Plc (Blend) in 2018 which has grown to provide committed facilities to 33 housing associations totalling over £1.9bn. In February 2025, the organisation announced the launch of a groundbreaking £150m partnership with the National Wealth Fund (NWF) to finance retrofitting of affordable homes alongside its new lending vehicle THFC Sustainable Finance Plc (TSF).
About Your Role
The Senior Data Analyst will lead the design, automation and delivery of high-quality data products that unlock actionable insight for internal teams and external clients. They will own the end-to-end analytics lifecycle – from architecting robust SQL data models and pipelines, through advanced Python- and VBA-driven analysis, to building sophisticated Power BI dashboards and executive-ready reporting. Operating at the intersection of data engineering, business intelligence and commercial strategy, the role will translate large, complex datasets into clear narratives that support decision-making, business development and market analysis, while standardising data across disparate systems to enable scalable, repeatable analytics solutions.
The role reports to the Senior Director, Strategy, who manages digital strategy, IT, marketing, brand, and communications for the organisation.
1.Key Responsibilities:
Data Analysis & Modelling
Maintain and query large datasets using advanced SQL techniques
Design and develop complex relational SQL data models
Perform comprehensive data analysis to identify trends and insights
Create and maintain robust data pipelines for continuous data processing
Data Visualisation & Reporting
Build and deploy interactive Power BI dashboards providing real-time insights to stakeholders
Design compelling data visualisations that translate complex datasets into actionable intelligence
Develop executive-level reporting solutions for internal teams, Board papers and client presentations
Client & Stakeholder Engagement
Collaborate with cross-functional teams to understand business requirements and deliver tailored solutions
Support business development activities through data-driven insights, customer and market analysis
Present findings and recommendations to senior stakeholders, using clear storytelling to influence decisions and drive adoption of data products
Data Integration
Standardise data across disparate systems with varying structures to support consistent analytics, reporting and performance tracking
Define and implement robust data validation, monitoring and documentation practices in line with good data governance principles
Work closely with IT and business teams to improve data capture, data definitions and metadata, ensuring long-term integrity of core datasets
Leadership & ways of working
· Lead analytics projects end-to-end, from scoping and prioritisation through to delivery, stakeholder sign-off and embedding into business processes
· Establish and champion best-practice standards for data modelling, visualisation, automation and quality across the organisation
· Coach and upskill colleagues to increase data literacy and self-serve capability, through training, documentation and pair-working
· Stay up to date with emerging tools, techniques and regulation relevant to data in financial services and housing, and proactively propose improvements to The Housing Finance Corporation’s data environment
Candidate Profile
1.Experience
· 5+ years’ experience as a Data Analyst (or similar role) in a corporate environment
· Financial services, capital markets and/or affordable housing / real estate industry experience strongly preferred
· Proven track record of working with large, complex datasets to deliver insight that supports business decisions
· Experience leading multi-stakeholder analytics projects and engaging confidently with senior decision-makers
Technical
SQL: Advanced querying capabilities, including complex joins, stored procedures and performance optimisation
Python & VBA: Strong programming skills including pandas, data manipulation libraries and proficient in Excel automation and macro development
Power Automate & SharePoint: Proficient in automated ETL workflows, data sync flows with error handling, SharePoint list connectors, and Power BI/Power Apps integration for live refresh and database write-back.
Power BI: Expert-level skills including:
Advanced DAX formula writing and optimisation
Complex data modelling and relationships
Custom visualisations and dashboard design
Row-level security implementation and access management
Power Query for data transformation and integration
Calculated columns and measures
Performance tuning and optimisation
Database & Development
Experience designing and implementing relational data models and working with database development teams
Understanding of and experience in implementing data governance principles
Analytical & Communication
Strong analytical thinking and structured problem-solving abilities, with a focus on business impact
Excellent written and verbal communication skills, with the ability to translate technical concepts for non-technical stakeholders
Detail-oriented with strong quality assurance practices
3. Qualifications
· Degree in data science, statistics, mathematics, computer science, economics or another quantitative discipline (or equivalent professional experience).
· Postgraduate or professional qualification in analytics, data, finance or a related field (for example MSc Data Science, CFA, ACA, FRM, MBA) is advantageous.
4. Benefits
· Pension scheme: We’re committed to helping you plan for the future. Our contributory pension scheme enables you to invest in your retirement, with The client matching your contributions to help your savings grow faster.
· Private medical insurance: Your health matters to us. Through Bupa private medical cover, you’ll have access to prompt, high‐quality healthcare, giving you reassurance and support when you need it most.
· Health support: Everyday health costs can add up, so our SimplyHealth plan helps towards dental, optical and physiotherapy expenses, as well as a range of wellbeing treatments — supporting your health inside and out.
· Annual leave: Time away from work is essential for balance and wellbeing. You’ll receive 25 days’ annual leave, increasing by one day each year (up to 30 days), plus an additional wellbeing day to recharge and your birthday off to celebrate in your own way.