At a Glance
- Tasks: Lead the design and delivery of analytics, data modelling, and AI solutions.
- Company: Join the world's largest independent renewable energy company focused on zero carbon energy.
- Benefits: Enjoy a competitive salary, health benefits, and opportunities for personal and professional growth.
- Other info: Diverse and inclusive workplace with excellent career advancement opportunities.
- Why this job: Make a real impact in the renewable energy sector while working with cutting-edge technology.
- Qualifications: Experience in data analytics, AI, and strong leadership skills required.
The predicted salary is between 70000 - 90000 £ per year.
Do you want to work to make Power for Good? We're the world's largest independent renewable energy company, guided by a vision to create a future where everyone has access to affordable, zero carbon energy. Achieving our ambitions would be impossible without our people, who are our most important asset. We continually invest in them.
RES is a family with a diverse workforce, dedicated to the personal and professional growth of our people, no matter what stage of their career they're at. We promise rewarding work that makes a real impact, the chance to learn from inspiring colleagues across a growing global network, and opportunities to grow personally and professionally. Our competitive package offers a wide range of benefits and rewards.
Job Summary
The Reporting, Analytics and AI Lead owns the design and delivery of analytics, data modelling, reporting, and AI-enabled consumption use cases through the enterprise data platform. This pivotal role is responsible for designing and delivering scalable, secure, and future-ready data modelling, reporting, and analytics through Azure, Fabric, and Purview, serving as the single source of truth for the enterprise. The role empowers business users to consume trusted, governed, and explainable data products through reporting, semantic models, and approved AI-enabled analytics tools. This is a technical delivery role focused on quality data, AI, and analytics through the data platform—not a traditional BI role or general enterprise AI function.
Key Accountabilities
- Lead the design and delivery of trusted data, technical specifications, and data models across Azure, Fabric, and Purview to provide integrated, secure, and scalable data for consumption.
- Own and deliver analytics, reporting, and AI-enabled consumption requirements.
- Define, document, and validate reporting requirements, KPI definitions, business rules, management information logic, and analytics use cases.
- Partner with stakeholders to shape use cases, success measures, and iterative delivery plans.
- Deliver reporting, AI, and analytics outputs that are trusted, governed, consistent, and suitable for senior stakeholder consumption.
- Lead AI tools to answer business questions using approved, certified, and traceable data products.
- Validate AI for accuracy, context, source, assumptions, business meaning, and appropriate use.
- Deliver and integrate AI-enabled analytics and data science capabilities.
- Identify opportunities to implement outputs that reduce manual reporting and replace with governed data products, semantic models, and AI-enabled analytics consumption.
- Manage stakeholder expectations, prioritisation, adoption, feedback, and reporting rationalisation.
- Support the transition from dashboard-led reporting to governed data products, semantic models, and AI-enabled consumption through the data platform.
- Ensure AI-enabled analytics outputs are explainable, traceable, and aligned to approved metric definitions.
- Work with platform, governance, engineering, and modelling colleagues to ensure AI-enabled consumption is safe, controlled, and operationally supportable.
Core Skills
- Expertise in semantic data modelling, including physical, dimensional, and logical models with deep understanding of BI patterns and enterprise architecture.
- Highly skilled in building consistent metrics and reporting layers across governed platforms.
- Advanced technical skills in hands-on delivery using Microsoft Azure, Fabric, and modern tools to deliver quality data through a data lakehouse.
- Strong data visualisation and UX delivery; ability to critique and uplift data and reporting quality.
- Strong reporting, analytics, and management information capability.
- Strong AI-enabled analytics, natural language querying, semantic consumption, and delivery of explainable analytical outputs.
- Ability to validate AI-generated analytical answers for accuracy, context, assumptions, source data, and business meaning.
- Working knowledge and skills in data science, AI, and machine learning applications in analytics and reporting, including responsible use controls.
- Ability to work with engineers and modellers to translate business requirements into governed data products and semantic models.
- Skills in semantic models, certified datasets, controlled self-service analytics, and AI-enabled consumption patterns.
- Understanding of data sensitivity, access controls, governance requirements, and responsible use of AI-generated outputs.
- Leadership, coaching, stakeholder, and mentoring skills.
- Passion for data and innovation to implement global best practice in modern, scalable, and future-proof reporting and analytics.
Required Experience
- Bachelor's degree in data analytics, data science, or related field.
- Extensive experience in data, AI, and analytics delivery with a proven track record of delivering secure, high-value data, AI, and analytics products and measurable business impact.
- Proven experience in semantic data model delivery.
- Experience in leadership and line management; must have worked in a technical data team, mentored and led other team members, and worked with a Chief Data Officer.
- Extensive experience implementing Microsoft Azure and self-service data platform frameworks at scale through the consumption layer.
- Experience in data standardisation frameworks for harmonising data definitions, taxonomies, and formats across regions.
- Experience translating business requirements into data products, semantic models, reports, or analytical outputs.
- Experience rationalising reports, metrics, dashboards, management information processes, and self-service analytics environments.
- Experience supporting senior stakeholders with trusted reporting and analytics; track record of delivering executive-certified data, AI, and analytics products with high adoption.
- Experience validating outputs for senior management or executive reporting.
- Experience delivering data science, advanced analytics, and AI-assisted analytics capabilities integrated with governed data platforms.
- Experience working closely with data engineers, architects, and business domain leads to design and deliver technical specifications and model design.
- Experience supporting AI-enabled analytics, natural language querying, automated insights, semantic search, or AI consumption layers.
- Awareness of relevant AI governance frameworks such as NIST AI Risk Management, ISO AI Management standards, Responsible AI principles, or equivalent enterprise control frameworks.
- Relevant analytics, data, Power BI, SQL, Microsoft reporting, Azure, AI analytics, or data platform certifications.
At RES, we celebrate difference as we know it makes our company a great place to work. Encouraging applicants with different backgrounds, ideas, and points of view, we create teams who work together to solve complex problems and design practical solutions for our clients.
Reporting, Analytics and AI Technical Lead in Glasgow employer: RES
At RES, we are committed to fostering a dynamic and inclusive work environment where every employee can thrive. As the world's largest independent renewable energy company, we offer competitive benefits, a culture of continuous learning, and ample opportunities for professional growth, all while contributing to a sustainable future. Join us in making a meaningful impact through innovative data solutions in a collaborative global network.
StudySmarter Expert Advice🤫
We think this is how you could land Reporting, Analytics and AI Technical Lead in Glasgow
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RES!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RES.
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We think you need these skills to ace Reporting, Analytics and AI Technical Lead in Glasgow
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RES, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RES. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RES
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RES!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
