IT Supervisor / Retail Applications

Bachelor's degree in a relevant field; a Master's degree in Data Science, Artificial Intelligence or a related discipline is a plus, Minimum 5 years of hands-on experience in data engineering and/or business intelligence, Has led end-to-end data or BI projects — from requirement analysis through delivery — taking full ownership of scope, timeline and quality in close collaboration with stakeholders, Has actively managed vendor relationships: coordinating scope, tracking deliverables and escalating issues in alignment with senior stakeholders, Experience in a multi-entity or multi-country data environment is a strong advantage, Strong command of SQL / T-SQL; able to write complex queries, stored procedures and performance-tune them with confidence, Advanced Power BI skills including tabular model design, DAX and report performance optimization, Hands-on ETL development and management experience with SSIS or comparable tools, Solid understanding of DWH design principles (Star Schema, Medallion / layered architecture), Data quality mindset: experience designing and operating source-to-target reconciliation, anomaly detection and automated controls, Experience with cloud data platforms (Azure — Event Hubs, Stream Analytics, Data Factory, Synapse; or Google Cloud Platform — BigQuery) is a strong advantage; familiarity with real-time or streaming data pipelines is a plus, Working knowledge of Python for data engineering and analytics is an advantage; interest in applying AI and machine learning in retail contexts — such as demand forecasting, segmentation or anomaly detection — is a plus, Strong analytical thinking: able to derive meaning from data and translate findings into business language, Good command of written and spoken English, Strong business follow-up, process accountability and stakeholder communication skills. Job Description: Lead the development and maintenance of ETL pipelines feeding the data warehouse built on Medallion architecture (Bronze / Silver / Gold layers), Design and develop advanced Power BI reports and dashboards that drive operational and strategic decisions across a large-scale, multi-country retail operation, Own the data integrity across transformation layers — from source system to final report — and drive data quality as a continuous process, Establish and operate source-to-target reconciliation processes; build automated data quality checks and alerting mechanisms, Manage external vendors on ETL and data model development: define scope, track deliverables, control timelines and enforce quality, Coordinate and oversee BI and data engineering projects end-to-end — from requirement analysis through to delivery, Conduct exploratory data analysis (EDA) on new datasets and lead feature preparation for machine learning use cases, Collaborate on retail-focused analytics initiatives: demand forecasting, customer segmentation, basket analysis and churn, Contribute to data governance practices: data dictionary, documentation standards and data quality KPI reporting, Provide technical mentorship to the BI & Data Engineering Specialist; support the team's growth in new technologies and methodologies, Maintain and develop strong cross-functional relationships with business units, IT teams and regional stakeholders.