Data Analyst

Assignment Description

We are seeking a Data Analyst for an assignment requiring on-site attendance three days per week. The work covers enterprise reporting, analytics engineering and data engineering in a retail environment. You will contribute across teams in a platform-building environment where standards and processes are still evolving.

Mandatory Qualifications

Retail Knowledge and Business Analysis

• A good understanding of retail operations, business processes and reporting requirements.
• Experience working with retail sales, point-of-sale (POS) transactions, product and store hierarchies, stores, markets and customer-related data.
• An understanding of retail KPIs, including net and gross sales, transaction counts, average transaction value, basket size, product performance and comparable sales.
• Experience analyzing retail transactions, conducting market basket analysis and assessing sales trends.
• An understanding of retail operations across multiple markets, franchisee reporting and consistent KPI definitions across business entities.
• The ability to translate retail terminology and business requirements into reliable analytical measures, reporting solutions and practical analytical solutions.

Governance, Security and Solution Quality

• Experience modernizing reporting and migrating enterprise BI solutions.
• Knowledge of governed self-service analytics, data contracts and data-product principles.
• Proven experience designing reliable analytical solutions, validating data and optimizing report performance.
• Experience with access control, object-level security (OLS) and row-level security (RLS) in Microsoft Fabric and Power BI.

Power BI, DAX and Data Modeling

• Strong experience designing semantic models and applying dimensional modeling, including star schemas, relationships, cardinality, and fact and dimension tables. A strong understanding of semantic-model optimization is also required.
• Experience building certified semantic models that can be reused for governed self-service analytics.
• Extensive experience in the design and development of enterprise Power BI solutions, supported by strong hands-on expertise in semantic modeling, report design, governed self-service analytics and workspace management.
• Expert-level proficiency in DAX, encompassing performance optimization, calculation groups, time intelligence, row context, advanced filter context, and complex measures and business calculations.
• Experience using the M language and Power Query for data transformation.

Collaboration and Communication

• Experience collaborating with business and technical teams in an agile environment, with the ability and willingness to contribute across teams.
• Strong documentation, communication and knowledge-sharing skills, including the ability to communicate effectively with business and technical stakeholders.

Experience and Language

• At least six years of relevant experience in BI, analytics engineering or data engineering.
• Excellent communication skills in English.

Microsoft Fabric and Data Engineering

• Experience working with modern data platforms such as Azure Data Factory, Databricks, Azure Data Lake or comparable platforms.
• Experience applying Bronze, Silver and Gold data-layer patterns and working with data lake architecture and Delta Lake.
• Familiarity with version-controlled analytical assets, CI/CD, deployment pipelines and Git integration.
• Strong proficiency in SQL for data validation, troubleshooting, transformation and analytical queries.
• A strong analytics-engineering mindset that prioritizes maintainable, testable, version-controlled and reusable analytical assets.
• Practical Microsoft Fabric experience spanning notebooks, Dataflows Gen2, Data Pipelines, Warehouse and Lakehouse, or strong experience with Power BI and Azure data platforms together with a demonstrated ability to become productive in Fabric quickly.
• Practical experience using PySpark and Python to develop solutions for data engineering, transformation and distributed data processing.
• An understanding of Import models, DirectQuery and Direct Lake, including the performance and architectural considerations of each.

It is considered an advantage if you have familiarity with customer loyalty, retention, segmentation and customer behavior analytics. Relevant Microsoft certifications, such as PL-300 or DP-600, are also considered an advantage. Experience developing Python and PySpark solutions specifically within Microsoft Fabric or Databricks is preferred.