Data Engineer

İş Tanımı

Responsibilities

• Collaborate with BI Development, Business Units, Software Development and Data Science teams to understand data requirements
• Build and maintain a high-performance, scalable modern data platform on Microsoft Fabric (Lakehouse, Warehouse, OneLake, Data Factory and Spark).
• Design, build and maintain scalable and reliable data pipelines for ingesting and transforming data from multiple enterprise systems.
• Migrate existing Oracle DWH objects and legacy ETL jobs to Fabric-native pipelines and T-SQL
• Build and maintain reliable data ingestion from SAP and other retail source systems (POS, e-commerce, ERP, WMS)
• Design dimensional data models that serve Power BI semantic models efficiently
• Deploy data optimizations and rules to ensure data quality, consistency and accuracy
• Monitor and optimize data storage, query performance and pipeline execution to ensure scalability, reliability and cost efficiency.
• Ensure best practices and standards are followed in all data engineering tasks

Required Qualifications

• Bachelor's degree in Computer Science, Computer/Software Engineering, Mathematical or Industrial Engineering, Statistics or a related quantitative field, or equivalent practical experience
• 4+ years of professional experience in data engineering
• Strong SQL development skills - T-SQL and PL/SQL, including performance tuning
• Experience in ETL design, implementation and maintenance
• Experience in schema design and dimensional data modeling
• Hands-on experience with Microsoft Fabric, ideally as part of a migration from a legacy DWH/ETL stack
• Solid Python, PySpark and Spark SQL development skills.
• Retail domain experience
• Strong problem-solving and analytical abilities
• Good communication and collaboration skills

Preferred

• Familiarity with enterprise ETL tools (Talend, Pentaho, ODI, Informatica) - useful for understanding our current landscape
• Oracle DWH and MicroStrategy-to-Power BI migration experience
• Power BI semantic modeling and DAX knowledge
• Cloud data platforms, particularly Azure (Data Factory, Synapse, Databricks, DevOps)
• Microsoft DP-700 and/or DP-600 certification
• Experience with Git-based development and CI/CD (Azure DevOps is preferred).
• Experience integrating data from SAP R/3 and SAP HANA (Datasphere is a plus)