Data Engineering Manager (Databricks)

What is this position about?

- Design, build, and maintain semantic layers and KPI models using Databricks Metric Views to underpin governed executive scorecards and AI-powered analytical solutions.

- Work directly with business owners to define, validate, and translate KPI requirements into reusable data models and business logic.

- Profile source data quality, ownership, data grain, and reconciliation requirements across enterprise source systems.

- Design and implement data integration and transformation pipelines that prepare enterprise data for AI-generated narratives and conversational analytics.

- Define conformed dimensions and market-specific data variations to support multi-market reporting and analytics.

- Collaborate closely with Business Analysts and AI Engineers to align KPI definitions with underlying data structures and business ontologies.

- Establish and enforce data quality, validation, and monitoring frameworks across all data assets feeding analytical applications.

- Implement security, access control, and governance practices aligned with platform and AI governance standards.

- Lead technical documentation and knowledge transfer initiatives at the conclusion of each delivery phase.

- Support production readiness assessments and oversee the deployment of solutions to production environments.

- 7+ years of experience in Data Engineering, with demonstrated expertise in semantic layer and KPI/metric modeling.

- Strong hands-on experience building and maintaining Databricks Metric Views or equivalent semantic/metric layer tooling.

- Advanced proficiency in SQL and Python for data processing, transformation, and pipeline development.

- Solid understanding of cloud data platforms, specifically Azure Databricks, and modern ELT/ETL tooling.

- Demonstrated expertise in data modeling techniques, conformed dimensions, and Medallion-style architectures.

- Experience profiling data quality, lineage, and reconciliation across multiple source systems.

- Comfort working directly with business stakeholders to gather, validate, and implement KPI requirements.

- Understanding of business ontology and semantic modeling concepts.

- Proficiency with Git version control and collaborative development practices.

- Knowledge of how data engineering supports AI/LLM-based analytics, including feature preparation for narrative generation and conversational analytics.

- Experience with FMCG/CPG or retail data ecosystems (POS, SKU, category, and market performance datasets) is a plus.

What about languages?

English: Advanced (required for effective communication with global teams)
How much experience must I have?

7+ years of experience in Data Engineering or related disciplines such as Data Architecture or Analytics Engineering, with demonstrated expertise in semantic modeling, KPI development, and multi-source data integration.
Our Perks and Benefits:
Every day lunches! (headquarters):

- Vegetarian, vegan, gluten and sugar free options.

- Gourmet meals every Friday with our on-site chef!

⚖️ Flexible working options to help you strike the right balance.

💻 All the equipment you need to harness your talent (Macbook and accessories).

🍎 Snacks and beverages available everyday (headquarters).

🎉 After office events, football, tennis and game nights (headquarters).

⚽ Everyone is welcome to join our football league every Wednesday's and Friday's.

🎱 Challenge your teammates to a pool game and win the office's trophy!

🎾 Tennis courts available for friendly matches.

🎮 Not a sports person? Don't worry, we also have chess championships, game and music nights for you to join!
📚 Learning opportunities:

- AWS Certifications (we are AWS Partners).

- Study plans, courses and other certifications.

- English Lessons.

- Learn from your teammates on our Tech Tuesdays!

🧭 Mentoring and Development opportunities to shape your career path.
🎁 Anniversary and birthday gifts.

📍 Great location and even greater teammates!