Data Manager - New Team - Unique NFP

hireful
Surbiton
9 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst Apprenticeship

Senior Data Engineer — Azure Data Pipelines & BI (Hybrid)

Data Engineer

Data Analyst/Consultant

HR Systems and Data Analyst

HR Systems and Data Analyst

Would you like to work in truly unique historic beautiful surroundings to work in? Manage a brand-new team and a greenfield project developing a new cloud-based data platform? Work for a NFP with a globally recognised brand and an amazing a flexible work culture as well as hybrid (2 days office working). A charity that can offer great benefits and give you free access to some of the most sort after attractions in the UK? If so, please read on ....Role - Data Manager aka Data & Analytics Manager, Data Lead, BI Manager, Data Platform Manager, Data Architect, Data GovernanceLocation - SW London / Surrey Borders - 2 Days office rest work from homeSalary - 60 - 64K (Annual pay increase pending) + 11% Pension + Bonus + 25 days rising to 29 days + Some amazing freebies The role You will be leading a small team of Data Engineer & BI Analyst looking at implementing a new cloud-based data platform overseeing all aspects: Data Strategy, Governance, Analytics and the Data Warehouse while helping to build a data driven culture across the business. The goal is to centralise previously siloed data across many different business units. There will also be support with some contract specialists / data focussed Project / Program Managers during the implementation phase.YouThey seek people with experience of leading teams and quite well-rounded experience of Data including:Understanding of Data Warehouse Architecture, Data Governance, Data Security FrameworksExperience with Cloud Platforms (e.g. Azure, AWS, GCP) and tools (e.g. Snowflake, Redshift, Azure Synapse)Data Visualisation e.g. Power BI, Tableau, LookerThe charity typically leans towards Microsoft solutions so this are the more likely to be deployed.Great opportunity to join a fantastic organisation I place where people truly enjoy working and people I have placed seem to stay for the long term.Interested? Please send a cv for a swift response

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.