Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Analyst Water

Manchester
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Clean Rivers and Seas Data Analyst

Funds Technology – Data Analyst Manager/ Assistant Manager/ Senior Consultant

Senior Business/Data Analyst- Asset Management

Senior Business/Data Analyst- Asset Management in London

Senior Data Scientist

Senior Data Analyst - Water

Salary: circa £50k 

Location: Hybrid – Manchester

Contract: Fixed Term 3 months (with potential extension to 6 months)

The Vacancy

Multitask Personnel are working with a company at the forefront of energy and utility innovation. They own and manage essential energy infrastructure assets that offer smarter energy solutions for all.

Through smart metering, installation, data services, EV charging infrastructure, and the electrification of heat, they are creating a more sustainable future. As they expand their capabilities in managing SMART water meters, we are recruiting a highly skilled Senior Data Analyst to lead the design and development of robust processes, systems, and data strategies that support operational excellence.

If you're passionate about data, thrive in dynamic environments, and want to shape the future of utilities, this is the opportunity for you.

The Role

As the Senior Data Analyst, you will play a pivotal role in driving the success of the company’s SMART water meter project. Your responsibilities will include:

•    Process Development: Defining interfaces, data transfer standards, and end-to-end processes for water meter data between multiple third parties.

•    Data Management: Ensuring data consistency, accuracy, and completeness across external parties.

•    Systems Implementation: Collaborating with IT to define system and data requirements, enabling financial and performance analysis at the asset level.

•    Analysis and Reporting: Creating dashboards, reports, and visualizations to monitor contract performance and data quality.

•    Stakeholder Engagement: Partnering with project managers, operational teams, and IT to translate business challenges into effective solutions.

Key Responsibilities

•    Develop processes to support the ownership, installation, and management of SMART water meters.

•    Lead GAP analysis to identify areas for improvement in current processes and data systems.

•    Design, implement, and monitor data validation processes to maintain data quality.

•    Document and communicate data insights to stakeholders at all levels.

•    Define customer journeys and external interfaces while maintaining GDPR compliance.

•    Support user acceptance testing, training, and smooth project transitions to BAU.

The Ideal Candidate

We are looking for someone with a proven track record in data analysis, process development, and stakeholder collaboration.

•    Background in the metering, water, or energy industries is desirable.

•    Extensive experience in data analysis for large/complex projects or programs.

•    Strong analytical and problem-solving skills, with experience in business process modelling and data analysis.

•    Ability to create comprehensive documentation such as business cases, requirements specifications, and cost/benefit analyses.

•    Proficient in Microsoft Office tools, including Excel, PowerPoint, and Visio.

•    Excellent communication and stakeholder management skills, with leadership capabilities.

•    Familiarity with Agile methodologies, UAT processes, and data security issues.

•    Understanding of the energy industry landscape.

To apply for this role, please send your CV to (url removed)

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.