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About the Role
Build and develop the data foundation for commercial analytics, translating business needs into reusable data models, metrics, and data products. You will own the Commercial data domain's analytics architecture, quality, and documentation, ensuring data is structured for future AI and GenAI use cases.
Responsibilities
- Build and maintain Silver and Gold-layer data products for the Commercial domain in Databricks.
- Turn enterprise data into reliable, reusable models, metrics, and datasets for reporting and analytics.
- Understand business needs and translate them into clear data definitions, KPIs, and scalable analytical solutions.
- Align Commercial data products with the enterprise data platform, architecture, pipelines, and engineering standards.
- Own data quality, documentation, lineage, and governance for key Commercial datasets and metrics.
- Ensure consistent definitions and trusted reporting across the business.
- Investigate data and BI issues across source systems, transformation layers, and reporting.
- Replace recurring manual fixes with sustainable data-model or transformation improvements.
- Help establish analytics engineering standards and AI-ready data foundations.
- Improve modelling, testing, documentation, and reuse.
- Support future advanced analytics and GenAI use cases.
Requirements
- 7+ years of experience across Analytics Engineering, Data Engineering, Business Intelligence, or related areas, with hands-on technical experience.
- Solid experience designing and building enterprise analytical data models, Silver/Gold data layers, and reusable datasets.
- Advanced SQL skills, including complex transformations, data modelling, query optimisation, and troubleshooting.
- Experience with dimensional and semantic modelling and modern cloud data platforms (Databricks, Snowflake, BigQuery, or Microsoft Fabric).
- Experience translating business requirements into scalable data solutions, working directly with business stakeholders and closely with Data Engineering, BI, and Analytics teams.
- Experience with PySpark, dbt, Python, data governance/cataloguing, or CI/CD is an advantage.
- Experience working with commercial data (CRM, sales, marketing, or customer data) is valuable.
Skills
- Databricks
- SQL
- Dimensional Modelling
- Semantic Modelling
- PySpark
- dbt
- Python
- Data Governance
- Data Cataloguing
- CI/CD
Location
- Berlin, Germany
- Oslo (Lysaker), Norway
- Stavanger, Norway
- Vindafjord (Nedre Vats), Norway
Work Type
- Full-time
Experience Level
- Senior
- 7+ years
Benefits
- Health insurance
- Generous pension plan
About the Company
- A collaborative & inclusive culture that celebrates and values everyone's contributions, encouraging diverse perspectives in decision-making.
- Prioritizes mental and physical well-being.
- A creative and safe workplace within a company experiencing rapid growth.
- Stability of being Norway's first unicorn listed on the Oslo Stock Exchange.
- An international and supportive environment within a Norwegian multinational that values collaboration and innovation.
- Structured onboarding plan and career opportunities within the company.