Data Governance and Controls Manager

E.surv
Kettering
2 months ago
Applications closed

Related Jobs

View all jobs

Data Governance & Enablement Manager

Data Quality and Governance Manager

Data Quality Manager

Business Intelligence and Database Lead

ECB Data Analyst

Data Analyst


Trading since 1989, e.surv Chartered Surveyors is the UK's number one residential surveyor and the largest provider of property risk expertise and residential surveying services. To put it into numbers, we complete more than one property inspection every 12 seconds and employ over 600 surveyors from Lands End to John OGroats and Northern Ireland. This gives us the flexibility to offer nationwide coverage combined with invaluable local knowledge.



We're part of the LSL Property Services Group PLC which includes household names Your Move and Reeds Rains as well as the mortgage network PRIMIS. We work with lenders, intermediaries, social housing entities and estate agents in addition to private customers.


We are currently recruiting for a Data Governance and Controls Manager.

Role Purposes

This role is a key managerial position within e.survs Data Management function, responsible for implementing and enhancing the organizations Data Governance Framework. The Data Governance Manager will oversee the management and control of data throughout its lifecycle, ensuring compliance with corporate and regulatory standards. The individual will play a crucial role in supporting compliance e...

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.