

Ea Change
Financial Data Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Financial Data Analyst with a 4-month contract at £650/day inside IR35, located in Gloucestershire (twice/week onsite). Requires a qualified Accountant or Actuary, SQL proficiency, and experience in Finance functions.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
650
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🗓️ - Date
July 31, 2026
🕒 - Duration
3 to 6 months
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🏝️ - Location
On-site
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📄 - Contract
Inside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
Gloucestershire, England, United Kingdom
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🧠 - Skills detailed
#Datasets #SQL (Structured Query Language) #Leadership #Data Analysis
Role description
Role: Finance Data Lead
Rate: £650/day inside IR35 (via Umbrella)
Location: Gloucestershire (twice/week onsite)
Start date: Late August / Early September
Duration: 4-month initial contract (scope for extension)
We're seeking an experienced Finance Data Lead to join a leading Wealth Management client to provide business-critical financial information used across Finance and the wider organisation, including data supporting financial modelling, provisions, internal reporting and externally audited accounts
Key Responsibilities:
• Provide day-to-day leadership, support and technical guidance to a team of junior Financial Data Analysts, improving their financial understanding, SQL capability and overall quality of delivery.
• Review and approve the team’s work, including SQL code, data analysis and final financial outputs.
• Take professional ownership of financial data and numbers used within modelling, provisions, reporting and the statutory accounts.
• Translate requests from Finance and wider business stakeholders into clearly defined data requirements. Work closely with Finance, Actuarial, Data and Technology teams to produce reliable financial information.
Required experience:
• Qualified Accountant or Actuary, such as ACA, ACCA, CIMA, FIA or an equivalent recognised professional qualification.
• Experience working within a Finance function and taking ownership of financially material outputs.
• Practical SQL experience, including reading and reviewing queries, joining data from multiple sources and validating outputs. Experience working with large or complex financial datasets.
• Strong communication skills, with the ability to clarify ambiguous requests and explain complex data clearly.
Role: Finance Data Lead
Rate: £650/day inside IR35 (via Umbrella)
Location: Gloucestershire (twice/week onsite)
Start date: Late August / Early September
Duration: 4-month initial contract (scope for extension)
We're seeking an experienced Finance Data Lead to join a leading Wealth Management client to provide business-critical financial information used across Finance and the wider organisation, including data supporting financial modelling, provisions, internal reporting and externally audited accounts
Key Responsibilities:
• Provide day-to-day leadership, support and technical guidance to a team of junior Financial Data Analysts, improving their financial understanding, SQL capability and overall quality of delivery.
• Review and approve the team’s work, including SQL code, data analysis and final financial outputs.
• Take professional ownership of financial data and numbers used within modelling, provisions, reporting and the statutory accounts.
• Translate requests from Finance and wider business stakeholders into clearly defined data requirements. Work closely with Finance, Actuarial, Data and Technology teams to produce reliable financial information.
Required experience:
• Qualified Accountant or Actuary, such as ACA, ACCA, CIMA, FIA or an equivalent recognised professional qualification.
• Experience working within a Finance function and taking ownership of financially material outputs.
• Practical SQL experience, including reading and reviewing queries, joining data from multiple sources and validating outputs. Experience working with large or complex financial datasets.
• Strong communication skills, with the ability to clarify ambiguous requests and explain complex data clearly.






