Your mission We are looking for a Senior Analytics Engineer / Semantic Model Owner (Microsoft Fabric / Power BI) to help build and govern QBi's next-generation analytics foundation. This is not a report-factory role. The role exists to reduce one-off reporting effort by building reusable, governed and scalable data products : Microsoft Fabric data structures, Power BI semantic models, KPI definitions, validation rules, reporting patterns and renewable-domain data models that can be reused across customers, internal teams and future product modules. The idóneo candidate combines strong data modeling and Microsoft Fabric capability with data-quality discipline and the ability to translate industry-standard workflows into robust analytical structures. This person should be comfortable working with business stakeholders, product teams, data engineers, analysts and leadership. They must be able to distinguish between a one-off dashboard request and a recurring data-model need that should become part of QBi's reusable data foundation. Mission Your mission will be to turn QBi's renewable-energy knowledge into scalable data and semantic-model assets. You will be instrumental in showing how and helping QBi move from fragmented reporting and ad hoc BI execution toward a governed analytics layer that supports:
* Existing customer reporting and reporting modernization;
* Microsoft Fabric / Power BI semantic-model governance;
* Technical Analytics and data-quality logic;
* Data Model-as-Infrastructure / Renewable Data Foundation offers;
* Future AI-native product and operational workflows;
* Future Revenue Copilot and hybrid revenue intelligence products. What This Role Is — and Is Not This role IS
* a senior analytics engineering role;
* a semantic model ownership role;




* a Microsoft Fabric / Power BI governance role;
* a renewable-domain data-model role;
* a bridge between business needs, data structures and scalable analytics;
* a role that uses AI to accelerate analytics engineering, documentation and model review. This role IS NOT
* a generic Power BI report-builder role;
* an open-ended "stakeholder asks, we build a dashboard" role;
* a data-science key trends informed role;
* a deep ML engineering role;
* a generic Microsoft consulting role;
* a role that accepts unbounded custom work without converting it into reusable patterns. Key Interfaces This role will work closely with:
* Data Engineering;
* BI / Reporting;
* Product Builders;
* Architecture / Platform;
* selected external Fabric or data-platform specialists where needed. And from time to time with:
* Customer Operations and Professional Services;
* Commercial / KAM teams;
* future Revenue Copilot and Renewable Data Foundation owners;

Key Responsibilities
1. Own and evolve QBi's semantic model layer
* Design, maintain and improve reusable semantic models for Power BI and Microsoft Fabric.
* Define consistent KPI logic, measures, dimensions, hierarchies and analytical relationships.
* Maintain metric definitions, calculation logic and semantic-model documentation.
* Ensure business users, analysts and AI tools work from trusted semantic foundations.
* Review changes to key measures,



shared datasets and customer-facing analytical structures. 2. Build scalable data models in Microsoft Fabric
* Design conceptual, logical and physical data models for renewable-energy use cases.
* Work with Microsoft Fabric Lakehouse, Warehouse, semantic models and related data-engineering patterns.
* Translate renewable asset, portfolio, contract, event, revenue, reporting and data-quality concepts into scalable model structures.
* Collaborate with data engineers on ingestion, transformation and validation patterns.
* Support reusable Fabric architectures for internal and customer-facing use cases. 3. Reduce custom BI workload through reusable analytics assets
* Convert recurring reporting needs into reusable semantic models, templates, report families and governed data products.
* Challenge ad hoc report requests when the better answer is model improvement, template creation or self-service enablement.
* Build reporting structures that reduce manual BI customization.
* Help define which requests become product features, governed analytics patterns or bounded expert-service work. 4. Strengthen data quality, governance and trust
* Define validation rules, reconciliation checks, data-quality indicators and confidence signals.
* Classify and explain data-quality issues in operational and customer-facing contexts.
* Support lineage, data ownership, metric governance and semantic-model change control.
* Identify where data-quality limitations affect reporting, customer trust or product behavior.
* Ensure analytical outputs are explainable and defensible. 5. Support QBi's Renewable Data Foundation strategy
* Turn QBi's renewable-data knowledge into reusable data-model ...

📌 Senior Analytics Engineer (Ceuta)
🏢 QBI Solutions
📍 Ceuta