Senior Data Analyst

Role: Senior Data Analyst
Job Ref Id: JD-1312
Competence level: senior
Start date: 2026-11-15
End date: 2027-08-31
Extension option: Yes
Scope: 100%
Location: Malmo
Remote work: In-office
Language: English
Application deadline: 2026-11-06
Number of consultants: 1
Security clearance: No

About the assignment

We are looking for a Senior Data Analyst to our client in Malmö.

Responsibilities

- The scope of the consultant services is to assist client in:
- Strengthening end-to-end Business Insights delivery using Power BI and Microsoft Fabric.
- Designing governed, reusable semantic models and consumption-ready analytical solutions.
- Developing and optimizing complex DAX calculations, measures, and analytical models.
- Building scalable data transformations and analytical processing solutions using SQL, Python, and PySpark.
- Supporting reporting migration, CORE-related delivery, franchisee reporting, and self-service enablement.
- Translating retail business requirements into meaningful KPIs, reporting solutions, and actionable insights.
- Contributing to SSDP Gold-layer, certified semantic model, and governed-consumption standards.
- Improving data quality, performance, documentation, and knowledge sharing across Business Insights and SSDP.
- The main tasks in the assignment are as below:
- Design, develop, and maintain Power BI reports, dashboards, semantic models, and analytical datasets.
- Develop and optimize advanced DAX measures, calculated tables, and business calculations.
- Translate business requirements into scalable analytical models, measures, reports, and actionable insights.
- Design and implement dimensional data models, including star schemas, fact tables, dimensions, and relationships.
- Develop data transformation and processing solutions using SQL, Python, and PySpark, particularly within Microsoft Fabric.
- Use Microsoft Fabric capabilities, including Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2, notebooks, and semantic models.
- Build scalable and reusable analytical models aligned with governed data-product principles.
- Analyze retail business data covering sales, transactions, products, customers, stores, markets, and franchisee performance.
- Develop and maintain retail KPIs, including sales performance, transaction volumes, average transaction value, basket analysis, product performance, and comparable sales.
- Improve report performance, usability, data quality, security, and maintainability.
- Optimize Power BI semantic models, DAX queries, refresh performance, and Direct Lake or DirectQuery configurations.
- Establish standardized reporting practices, reusable components, and common data-modeling standards.
- Support legacy reporting migration, CORE-related reporting requirements, and historical data validation.
- Support testing, validation, release preparation, stakeholder demonstrations, documentation, and onboarding.
- Collaborate with SSDP to establish consumption-ready patterns, including Gold-layer standards, certified semantic models, and Direct Lake usage.
- Support franchisee onboarding, governed self-service analytics, and report access management.
- Work closely with business stakeholders to understand retail processes and ensure reporting solutions provide relevant business insights.
- Share knowledge, coach colleagues, and establish reusable documentation to reduce single-person dependencies.

Requirements

Mandatory

- Experience: Minimum six years of relevant experience in BI, analytics engineering, or data engineering.
- Power BI: Extensive hands-on experience designing and developing enterprise Power BI solutions, including report design, workspace management, reusable and certified semantic models, and governed self-service analytics.
- DAX: Advanced DAX skills, including complex business calculations, filter and row context, time intelligence, calculation groups, and performance optimization.
- Data Modeling: Strong experience with dimensional modeling, star schemas, fact and dimension tables, relationships, cardinality, and semantic-model optimization.
- Power Query: Experience with Power Query, M language, and data transformation.
- Microsoft Fabric: Hands-on experience with Fabric Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2, and notebooks, or strong Power BI and Azure data-platform experience with the ability to become productive in Fabric quickly.
- SQL: Strong SQL proficiency for analytical queries, data transformation, troubleshooting, and validation.
- Python and PySpark: Practical experience developing data processing and transformation solutions using Python and PySpark, preferably within Microsoft Fabric or Databricks.
- Data Architecture: Experience with Delta Lake, data lake architecture, Bronze/Silver/Gold data-layer patterns, and modern data platforms such as Databricks, Azure Data Lake, and Azure Data Factory.
- Storage Modes: Understanding of Direct Lake, DirectQuery, and Import models, including their architectural and performance considerations.
- Analytics Engineering: Experience building reusable, version-controlled, testable, and maintainable analytical assets, including Git integration, CI/CD, deployment pipelines, data-product principles, and data contracts.
- Security and Governance: Experience with row-level security (RLS), object-level security (OLS), access control, and governed self-service analytics in Power BI and Fabric.
- Performance and Quality: Proven experience with report and semantic-model performance optimization, data validation, and reliable analytical solution design.
- BI Modernization: Experience with enterprise BI migration and reporting modernization.
- Retail Business Knowledge: Good understanding of retail operations, sales and POS transactions, product and store hierarchies, markets, customer data, and reporting requirements.
- Retail Analytics: Experience with retail transaction analysis, market basket analysis, sales trends, and KPIs such as net sales, gross sales, transaction count, average transaction value, basket size, product performance, and comparable sales.
- Multi-Market Retail: Understanding of multi-market retail operations, franchisee reporting, and consistent KPI definitions across business entities.
- Business Engagement: Ability to translate retail business requirements and terminology into reliable analytical measures and reporting solutions, and communicate effectively with business and technical stakeholders.
- Collaboration: Experience working in agile, cross-functional teams, with strong documentation, communication, and knowledge-sharing skills.
- Cross-Team Contribution: Ability and willingness to contribute across Business Insights and SSDP, with approximately 20–30% allocation to the secondary team as required.
- Adaptability: Comfortable working in a platform-building environment where standards and processes are evolving.

Nice-to-have

- Familiarity with customer loyalty, retention, segmentation, and customer behavior analytics is an advantage.
- Relevant Microsoft certifications, such as PL-300 or DP-600, are an advantage.