At a Glance
- Tasks: Design and govern data models for impactful reporting and analytics.
- Company: Join SEFE, a leading international energy company driving the future of sustainable energy.
- Benefits: Competitive salary, global opportunities, and a chance to shape the energy transition.
- Why this job: Make a real difference in energy security while honing your data modelling skills.
- Qualifications: Experience in data modelling, strong SQL skills, and a knack for translating business needs.
- Other info: Dynamic work environment with a focus on innovation and career growth.
The predicted salary is between 36000 - 60000 Β£ per year.
The Data Modeller is responsible for designing, evolving, and governing Gold-layer domain specific data models that power trusted reporting, analytics, and scalable self-service use across the organisation. This role blends deep data modelling expertise with strong analytical skills β translating reporting requirements and business questions into robust, performant, and reusable data structures that balance clarity for reporting with flexibility for ad hoc data exploration. The modeller acts as a critical bridge between Silver-layer data engineering patterns and business-facing consumption, ensuring that the resulting data models are intuitive, consistent, and future-proof while remaining aligned with enterprise standards and governance.
Responsibilities
- Gold-Layer Data Modelling & Design
- Design and maintain dimensional, denormalised, and semantic-ready Gold layer models optimised for BI, analytics, and self-service use
- Translate business concepts, KPIs, and analytical use cases into well-structured fact and dimension models
- Ensure models support both predefined reporting and ad hoc analytical exploration without rework
- Balance usability with extensibility β avoiding overfitting models to single reports or tools
- Consume curated Silver-layer data (e.g. Data Vault, 3NF, or conformed sources) and apply modelling patterns appropriate for Gold
- Clearly separate transformation concerns between Silver (integration and harmonisation) and Gold (consumption and insight)
- Ensure Gold models remain stable interfaces even as upstream sources evolve
- Contribute to architectural decisions on where business logic, calculations, and aggregations should reside
- Design models that are discoverable, intuitive, and safe for business self-service users
- Introduce appropriate genericity (e.g. conformed dimensions, shared metrics, reusable grain) to maximise reuse across domains
- Minimise report-specific logic by promoting canonical metrics and standard calculation patterns
What Will You Bring
- Comfortable working to tight timescales
- Strong experience designing analytics-ready Gold models within an Azure based medallion architecture
- Deep understanding of dimensional modelling concepts (facts, dimensions, grain, conformed dimensions)
- Proven ability to design models that support both operational reporting and exploratory analytics
- Advanced SQL skills for modelling, validation, and performance optimisation
- Experience supporting self-service BI platforms (e.g. Power BI), including interaction with semantic models
- Understanding of how upstream modelling choices (e.g. Data Vault, Silver transformations) impact Gold design
- Ability to translate ambiguous business questions into clear, reusable data structures
- Experience working in regulated or complex data environments an advantage
- Strong documentation and communication skills β able to explain modelling decisions to technical and non-technical audiences
About Us
Securing Energy for Europe β itβs a simple statement, with a bold ambition. SEFE is not just our name, but also encompasses everything that drives us. To accomplish this, weβre taking immediate action to secure gas supply β but also looking forward, to explore our role in the European energy transformation and how we can contribute to a stable and sustainable future. SEFE, an international energy company, ensures the security of supply and drives the decarbonisation of its customers. SEFEβs activities span the energy value chain, from origination and trading to sales, transport, and storage. Through its decades-long expertise in trading and the development of its LNG business, SEFE has become one of the most important suppliers to industrial customers in Europe, with an annual sales volume of 200 TWh of gas and power. Its 50,000 customers range from small businesses to municipalities and multinational organisations. By investing in clean energies and especially in the hydrogen ecosystem, SEFE is contributing to the energy transition. The company employs around 2,000 people globally and is owned by the Federal Government of Germany. Our international teams work across locations in Europe, Asia, and North America. Weβre passionate about energy and the important role it can play in shaping a better future. Securing energy β now and for the future.
Data Modeller in Manchester employer: SEFE Energy UK
Contact Detail:
SEFE Energy UK Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Data Modeller in Manchester
β¨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and analytics projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
β¨Tip Number 3
Prepare for interviews by brushing up on your SQL and modelling concepts. Be ready to discuss how you've tackled real-world problems and how your designs have made an impact in previous roles.
β¨Tip Number 4
Don't forget to apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at SEFE.
We think you need these skills to ace Data Modeller in Manchester
Some tips for your application π«‘
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with Gold-layer data modelling and Azure-based architectures. We want to see how your skills align with our needs, so donβt hold back on showcasing relevant projects!
Showcase Your Analytical Skills: In your application, emphasise your ability to translate complex business questions into clear data structures. We love seeing candidates who can bridge the gap between technical and non-technical audiences, so share examples of how you've done this in the past.
Highlight Your SQL Expertise: Since advanced SQL skills are a must for this role, make sure to include specific examples of how you've used SQL for modelling, validation, and performance optimisation. Weβre keen to know how youβve tackled challenges in previous roles!
Apply Through Our Website: We encourage you to submit your application through our website. Itβs the best way for us to receive your details and ensures youβre considered for the Data Modeller position. Plus, itβs super easy to do!
How to prepare for a job interview at SEFE Energy UK
β¨Know Your Data Models
Make sure you brush up on your knowledge of dimensional modelling concepts, especially facts and dimensions. Be ready to discuss how you've designed analytics-ready Gold models in the past, particularly within an Azure-based medallion architecture.
β¨Translate Business Needs
Prepare to demonstrate your ability to translate ambiguous business questions into clear, reusable data structures. Think of examples where you've successfully aligned data models with business requirements, ensuring they support both predefined reporting and ad hoc analysis.
β¨Showcase Your SQL Skills
Since advanced SQL skills are crucial for this role, be prepared to discuss your experience with modelling, validation, and performance optimisation. You might even want to practice some SQL queries beforehand to feel confident during technical discussions.
β¨Communicate Clearly
Strong documentation and communication skills are key. Be ready to explain your modelling decisions to both technical and non-technical audiences. Think about how you can simplify complex concepts and make them relatable to different stakeholders.