Senior Data Analyst Water

Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Data integrity

Lead Data Scientist[975963]

Data Scientist

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst - MMM / Econometrics

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)

Get the latest insights and jobs direct. Sign up for our newsletter.

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 Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.