Business Data Analyst (Retail Domain)

Location: Krakow, Poland

Core Data & Analytical Skills

• Strong experience in analysing large and complex datasets to identify retail trends, customer behavior, and actionable insights.
• Advanced proficiency in writing and optimizing complex SQL queries.
• Perform data validation to ensure accuracy, consistency, and integrity of retail data.
• Define and implement robust data quality checks and monitoring frameworks.

Data Discovery, Quality & Source Understanding

• Collaborate with cross-functional teams (business and technology) to evaluate ongoing initiatives and assess their impact.
• Document business processes, workflows, constraints, and use cases to support knowledge retention.
• Analyse new and existing retail data sources to evaluate structure, content, and readiness for analytics.
• Conduct detailed data investigations to identify lineage, anomalies, and inconsistencies.
• Design and execute data quality checks and validation processes.

Metadata Management & Enhancement

• Work closely with Data Engineering and business stakeholders to document key datasets, tables, and definitions.
• Perform metadata assessments to identify gaps in data definitions, lineage, and classifications.
• Define and maintain both business metadata (KPIs, retail metrics, glossary) and technical metadata (data types, source systems).
• Enhance metadata through analysis and collaboration across teams.
• Contribute to maintaining and improving data catalogues across internal and external retail data sources.

Data Modelling & Structuring

• Support the design and maintenance of logical and physical data models, particularly for curated and analytics-ready datasets.
• Recommend improvements to data models for better performance, scalability, and usability.
• Provide ad-hoc analysis to support retail initiatives such as merchandising insights, customer analytics, or data migration projects.

Additional Responsibilities

• Partner with Product Managers to deliver business outcomes aligned with retail objectives.
• Support business teams during UAT and post-production by resolving data-related queries and providing insights.
• Collaborate with Engineering teams to guide data design decisions based on business understanding.