Data Quality Analyst - Care Technology

Wandsworth
4 months ago
Applications closed

Related Jobs

View all jobs

Data Quality Analyst

Data Quality Analyst

Data Quality & BI Analyst

Data Governance & Quality Analyst

Senior Data Quality Analyst

Data Governance Analyst

Job Advertisement: Data Quality Analyst - Care Technology

Are you passionate about ensuring high-quality data in the care technology sector? Do you thrive in a collaborative environment where your analytical skills can make a real difference? If so, we want to hear from you!

Position: Data Quality Analyst - Care Technology
Contract Type: Temporary (3 months)
Hourly Rate: £20.03 - £21.70 PAYE or - £26.53 - £27.50 Umbrella
Location: Hybrid (Richmond & Wandsworth)
DBS Required: Yes

About the Role
Join our dedicated Care Technology team and play a pivotal role in transitioning from analogue to digital equipment for residents of Richmond and Wandsworth. As a Data Quality Analyst, you will provide comprehensive data support and quality assurance, ensuring that our datasets reflect the current service usage accurately.

Key Responsibilities

Lead and manage complex data quality and cleansing projects that enhance service delivery.
Systematically cleanse care technology datasets to maintain accurate records.
Collaborate with the Data and Performance Team and various stakeholders to improve data quality for individuals using care technology.
analyse and cleanse multiple datasets to identify service users who may no longer require care technology services.
Create and maintain a detailed audit trail for all cleansing activities.
analyse performance data to identify trends and compile insightful reports for management.
Produce and present analytical reports, using data visualisation techniques to engage diverse audiences.
Identify and resolve data errors through effective exception reporting and quality assurance processes.

What We're Looking For

Proven experience in data quality, cleansing, and management.
Strong analytical skills with a keen eye for detail.
Experience in stakeholder engagement and collaborative project work.
Proficiency in database management and data visualisation tools.
Ability to produce clear, concise reports and presentations.
A commitment to promoting equality, diversity, and inclusion in the workplace.

Why Join Us?

Be part of a team that is transforming care technology for the better!
Enjoy a flexible hybrid working environment.
Contribute to meaningful projects that directly impact the lives of residents in your community.
Collaborate with a team of dedicated professionals who value your expertise and insights.

How to Apply
If you're ready to take on this exciting challenge and help shape the future of care technology, we encourage you to apply today! Please submit your CV along with a brief cover letter outlining your relevant experience.

Join us in making a difference! Your analytical skills could be the key to improving the quality of care for countless individuals. We look forward to welcoming you to our team!

Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.

Adecco acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers. The Adecco Group UK & Ireland is an Equal Opportunities Employer.

By applying for this role your details will be submitted to Adecco. Our Candidate Privacy Information Statement explains how we will use your information - please copy and paste the following link in to your browser

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.

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.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.