EY - GDS Consulting - AI & DATA - Microsoft Fabric - Senior
at Ernst & Young
Posted 6 days ago
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- Compensation
- Not specified INR
- City
- Not specified
- Country
- India
Currency: INR
We are seeking a Data Engineer with 5-10 years of experience in data warehousing, ETL/ELT processes, data modeling, and cloud-based technologies, with a focus on Azure and Microsoft Fabric. The candidate will design, develop, and manage data solutions on the Microsoft Fabric platform, including Lakehouse, Data Engineering, Pipelines, Spark, Notebooks, and KQL Database. They will implement ETL/ELT processes, create and maintain data models for BI and analytics, and utilize Azure data storage services for effective data management. The role also involves writing and optimizing SQL, Python, PySpark, and Scala code, implementing DevOps practices and CI/CD pipelines, monitoring data pipelines, and collaborating with cross-functional teams to deliver data solutions that meet business needs.
At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
Job Summary:
We are looking for a Data Engineer with 5-10 years of experience in data warehousing, ETL/ELT processes, data modeling, and cloud-based technologies, particularly Azure and Fabric. The ideal candidate will have a strong background in building and managing data solutions within the Microsoft Fabric platform and will be proficient in various programming languages.
Key Responsibilities:
- Design, develop, and manage data solutions using Microsoft Fabric, including Lakehouse, Data Engineering, Pipelines, Spark, Notebooks, and KQL Database.
- Implement ETL/ELT processes to ensure efficient data integration and transformation.
- Create and maintain data models to support business intelligence and analytics initiatives.
- Utilize Azure data storage services (e.g., Azure SQL Database, Azure Blob Storage, Azure Data Lake Storage) for effective data management.
- Collaborate with cross-functional teams to gather requirements and deliver data solutions that meet business needs.
- Write and optimize code in SQL, Python, PySpark, and Scala for data processing and analysis.
- Implement DevOps practices and CI/CD pipelines for seamless data deployment and version control.
- Monitor and troubleshoot data pipelines to ensure reliability and performance.
- Communicate effectively with diverse teams to foster collaboration and knowledge sharing.
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