Your mission
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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:

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- 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

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- 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

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- 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:

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- Data Engineering;

- BI / Reporting;

- Product Builders;

- Architecture / Platform;

- selected external Fabric or data-platform specialists where needed.

And from time to time with:

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- 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

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- 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

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- 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

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- 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

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- 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. xqbhyrx

- Ensure analytical outputs are explainable and defensible.

5. Support QBi’s Renewable Data Foundation strategy

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- Turn QBi’s renewable-data knowledge into reusable data-model …

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📌 Senior Analytics Engineer / Semantic Model Owner (Microsoft Fabric / Power BI) (España)
🏢 QBI Solutions
📍 España