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About the role
We are seeking a skilled and experienced Data Engineer with strong expertise in Microsoft Azure technologies to design, develop, and maintain scalable data solutions. The ideal candidate will work closely with business stakeholders, Data AI teams, and IT governance teams to deliver high-quality data pipelines and reporting solutions. This role requires hands-on experience in handling large datasets, optimizing performance, and working with SAP and SQL-based data sources. Key Responsibilities 1. Data Engineering Development Design, develop, and enhance data engineering solutions based on business requirements. Build and maintain automated SQL-based data pipelines. Implement and optimize ETL/ELT workflows using Azure services. Ensure performance optimization and scalability of data solutions. 2. Data Processing Integration Work with large datasets from SAP and SQL databases. Implement business rules in collaboration with functional teams. Validate and ensure data accuracy, consistency, and reliability. Optimize data refresh cycles and query performance. 3. Documentation Governance Prepare and maintain: Data Dictionary Report Logic Documentation User Guides Follow data governance standards and IT compliance guidelines. 4. Collaboration Agile Practices Participate in Agile ceremonies including: Sprint planning Daily stand-ups Backlog grooming Coordinate with: Business stakeholders Data AI teams IT Governance team Track tasks, update progress, and manage risks/issues effectively. Technical Skills Required Azure Data Lake Storage (Gen2) Azure Databricks Azure Data Factory (ADF) PySpark / Python Advanced SQL Understanding of Lakehouse architecture Performance optimization techniques for large datasets Good to Have Experience working with SAP data Knowledge of Agile methodologies Experience with data gateways and enterprise data integration Experience Qualifications Bachelor s degree in Computer Science, Information Technology, Engineering, or related field. Proven experience as a Data Engineer in Azure environments. Hands-on experience with large-scale enterprise data solutions.
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