Sales Operations & CRM System Lead

Milton Keynes
10 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Sales Operations

Data Analyst / IT Support

Lead Data Engineer

Lead Data Engineer

Data Analyst ( hybrid) 3 days in office

Data Analyst - Excel & Operational insight

Sales Operations & CRM System Lead

Department: Sales HQ
Type of Position: Permanent
Location: UK
Reporting to: Sales HQ Manager 

About The Company
Imagine being part of a Global leader, where innovation and customer satisfaction drive everything we do. Join our Sales HQ team for an exciting new challenge.
Primary Objective: Increase sales productivity, effectiveness, and revenue.

The Role:
Join our client as Sales Operations & CRM System Lead; overseeing and optimising our CRM, providing valuable insights and analysis to help enhance the productivity and efficiency of our sales teams. You'll own and maintain data integrity and be responsible for mapping our sales processes.

Key Responsibilities:

CRM Management: Oversee and maintain, the development and utilisation of the CRM across the company. Ensuring data accuracy, correct coding, and usability.
Reporting & Analytics: Managing the development and maintenance of our BI reporting. Using this platform to provide insights to support decision-making.
Forecasting & Budgeting: Managing sales forecasting and budgeting processes.
Training and Support: Provide training and the supporting material to the sales teams on tools and processes.
Performance Metrics: Using objectives and key results to measure effectiveness of sales operations initiatives.
Management insights: provide insights on customer behaviour product sales gaps and pricing anomalies. 

Essential skills, education, and experience:

Degree or HNC/D in Business Administration, information management or related field.
Experience in Sales Operations, Sales data analysis or similar.
Experience with producing power BI data and reporting dashboards.
Proficiency with CRM systems and sales analysis.
Strong communication and presentation skills.
Basic/ intermediate commercial understanding of business.
Ability to work independently and manage time.
Willingness to learn about the business
Ability to meet deadlines.
Versatile attitude and a team player. 

Desirable skills, competencies, and experience:

Other qualifications to support Information Systems or Data analysis
Sugar CRM experience and data management including validation, data matching and quality control
Versatile attitude to take on different tasks.
Show a will to succeed and make things happen.
Be a willing part of a Team which has diverse responsibilities within the business
What We Offer:
We are continuously working to make our team even more diverse and inclusive. We welcome applications from all and are committed to attracting, recruiting and retaining the most talented individuals. They have sustainable development goals as we believe in caring for our futures as well as the future of the planet.

We offer a competitive and attractive package of benefits including, retail discounts, life assurance, Private Medical Cover, 25 days holiday including a holiday purchase scheme, a salary sacrifice personal pension plan and more!

The Selection Process: Upon successful application, candidates will be asked to undertake a first interview online followed by some online testing and lastly a second interview face-to-face, onsite at our clients Offices

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.