Marketing Data Analyst

Basingstoke
1 month ago
Create job alert

Our client is an established technology platform business seeking a Marketing Data Analyst to take ownership of reporting, insights, and data-driven decision-making across their marketing function. This role focuses on transforming data into compelling narratives that inform strategy, demonstrate ROI, and enable the marketing team to self-serve analytics. You'll work closely with their data engineering team who manage the core infrastructure, while you concentrate on extracting insights, building dashboards, and translating numbers into actionable intelligence for campaigns and commercial planning.

Location: Flexible working arrangements

THE MARKETING DATA ANALYST ROLE RESPONSIBILITIES WILL INCLUDE:

Extract and analyse data from the data warehouse using SQL, designing segmentation by geography and customer groups to support targeted campaigns and performance tracking
Develop compelling Power BI dashboards and reports that track campaign performance, lead conversion, and ROI for operational teams and C-suite executives
Map the complete customer journey from acquisition through conversion, identifying funnel bottlenecks and building models to assess campaign effectiveness
Transform complex datasets into narratives that fuel content creation, PR initiatives, and demonstrate platform value through engagement and revenue metrics
Partner with marketing, digital, finance, and data engineering colleagues to ensure reporting accuracy and enable self-service analytics capabilities

THE IDEAL MARKETING DATA ANALYST WILL HAVE:

Extensive experience developing marketing dashboards for senior leadership with strong Power BI expertise (advanced features like Co-Pilot desirable)
Solid SQL proficiency for data extraction plus familiarity with CRM systems and marketing platforms such as Salesforce and Marketo
Proven ability to translate technical data findings into clear, actionable business insights that inform strategy and optimisation
Strong collaborative approach working alongside data engineering and finance teams to align insights with business objectives
Curious, proactive mindset focused on storytelling through data with ability to identify trends, seasonal patterns, and growth opportunities

WHY JOIN THIS BUSINESS AS THEIR MARKETING DATA ANALYST?

Join a best-in-class marketing team led by an exceptional CMO with strong financial backing, recent marketing investment, and impressive growth trajectory offering genuine scope for personal and professional development
Flexible working culture with transparent company structure and collaborative, friendly team environment based in central Basingstoke (3 days per week office-based, easily accessible by car and train)
Armstrong Lloyd is a marketing specialist recruitment services provider. We specialise in the B2B SaaS space and have a variety of similar jobs available. We offer a personal service that will give you the best possible outcome in the recruitment process

Related Jobs

View all jobs

Marketing Data Analyst

Marketing Data Analyst

Marketing Data Analyst

Marketing Data Analyst: Insights & Self-Serve

Marketing Data Analyst

Marketing Data Analyst

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.

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.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.