Data and Analytics Officer

SNG (Sovereign Network Group)
Usa, SL4 4BQ, United Kingdom
Last month
£38,000 – £44,000 pa
Applications closed

Related Jobs

View all jobs

Data and Analytics Solutions Manager

SSA Digital Recruitment London, United Kingdom
£75,000 – £90,000 pa Hybrid

Data Architect (we have office locations in Cambridge, Leeds and London)

Genomics England London, United Kingdom
On-site

Director of Pricing, Data and Analytics

Datatech London, United Kingdom
£150,000 – £200,000 pa Hybrid

Senior Data Architect

Altro Norton, Hertfordshire, SG6 1AG, United Kingdom

Analytics Governance Analyst

Adecco London, United Kingdom
£690 pd Hybrid

Senior Technical Program Manager, Professional Services

Databricks London, United Kingdom
On-site

Salary

£38,000 – £44,000 pa

Job Type
Permanent
Work Location
Hybrid
Seniority
Mid
Education
Degree
Posted
30 Apr 2026 (Last month)

SNG (Sovereign Network Group) is one of the largest housing associations in England. We provide over 85,000 homes and invest in communities across the South, West and East of England, including London, as well as building thousands of new affordable homes every year.

We have a fantastic new opportunity as a Data and Analytics Officer in our Data, Analytics and AI department. In this new role you will work closely with stakeholders creating self-serve Power BI datasets to create high quality reports, published to the Power BI environment, ensuring accurate and timely delivery to meet the needs of the business.

You'll be based from our office in eitherBasingstokeor Wembley, you'll combine home and office working in line with our hybrid approach.

Responsibilities include

  • Develop and maintain interactive dashboards, reports, and data visualisations using Power BI to support decision-makers across the organisation.
  • Design and implement fact and dimension data models to ensure data accuracy, consistency, and efficiency in all SNG reporting and analysis.
  • Work closely with cross-functional teams to understand the data needs and provide analytics solutions to address specific business challenges.
  • Work with the Data & Analytics Manager to help champion and support the Centre of Excellence for Power BI.

What we need from you

  • Excellent knowledge of reporting software tools such as Sequel Server Management Studio, Data Warehousing Concepts, DevOps, Power BI.
  • Good understanding of star schema models and the use in Power BI.
  • Excellent communication skills and ability to adapt to a wide audience.
  • Ability to use SQL query to shape data requirements.

Industry Insights

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

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

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. 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.

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data Science Jobs UK 2026: roles, salaries and the trends shaping UK data science hiring over the next three years — from MLE crossover to GenAI workflows. Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.