Data Analyst - E-Commerce

Zachary Daniels Recruitment
Grosvenor Square, W1K 4AB, United Kingdom
Last month
Applications closed

Related Jobs

View all jobs

Data Analyst

Harnham - Data & Analytics Recruitment London, United Kingdom
£48,000 – £50,000 pa On-site

Data Analyst

Grove Talent Solutions Chippenham, United Kingdom
£28,000 – £35,000 pa On-site

Data Analyst

Lynx Recruitment London, United Kingdom
£40,000 – £65,000 pa On-site

Data Analyst

Sagacity London, United Kingdom
£40,000 – £60,000 pa Hybrid

Data Analyst

Healix Esher, United Kingdom

Data Analyst

Jackson Hogg Newton Aycliffe, United Kingdom
Posted
6 Mar 2026 (Last month)

Finance Business Partner - E-commerce | Large Multi-Site Retail Group

London

Hybrid | 2 Days in office

Salary £42,000 - £48,000

Our client is a large multi-site retailer and we need an experienced Finance Business Partner to join the E-Commerce team and deliver high-quality data & financial insight and support. You will be a bit of a pro when it comes to large sets of Data and have large retail, FMCG or Pharmaceutical background.

Reporting into the head of E-Commerce, they need a strong Analyst to connect the dots & alert for whats ahead.

Our client requires someone with extensive experience in Excel, VBA, Power Query & Power BI. Our client is a large, complex Retail Group with a large e-commerce platform & stores across the UK & Ireland.

This role is ideal for someone who thrives on data management and enjoys working with spreadsheets, while also business partnering across stakeholders to gain insight and up to date changes.

Skills required:

Essential:

Advanced Excel skills (formulas, pivot tables, data analysis).

VBA, Power Query & Power BI experience ideally

E-commerce or retail / product pricing experienceDesirable:

Familiarity with Power Query, basic formulas, auditing, or light data transformation workflows.

Interest in learning about data pipelines, integrations and automation.

Python or SQL experience

Finance Qualifications up to PQ - but not essentialDuties include:

Leading monthly forecasting, variance analysis and financial modelling

Automate data processes where possible using advanced Excel functions or VBA.

Use advanced Excel skills (VLOOKUP/XLOOKUP, INDEX/MATCH, pivot tables, Power Query, data validation, conditional logic) to transform, clean and prepare data.

Build and manage complex Excel spreadsheets for pricing analysis, margin tracking, and promotional planning.

Business partner with a wide range of teams across Finance, Marketing, Distribution Centres

Present weekly reports to senior stakeholders You will also:

Support and work closely with the head of E-commerce & partner with Finance, marketing and distribution teams to maintain strong relationships between all departments

Support the creation of streamlined data processes, so updates made in one area flow cleanly into others.

Assist with mapping data between systems (e.g., ERP, PIM, CMS, marketplace feeds).

Help maintain master data files and support the development of a 'single source of truth.'This is a fantastic opportunity for someone who enjoys variety and wants to play a key role in e-commerce team. You'll have the chance to shape processes and work on exciting data projects that drive business growth.

BH35368

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.