- Hybrid
- Full-time
$14.68 USD
Bangalore, भारत
Vacancy description
Rarefind HR consulting Pvt Ltd
Bombay, भारत
Senior Azure Data Engineer - AnalyticsExperience : 6 - 10 Years (Strict Requirement)Role Overview : We are seeking an experienced Senior Azure Data Engineer with a strong background in building scalable data pipelines, enterprise data modeling, and modern cloud architectures. The ideal candidate will bring deep expertise in Microsoft Azure, enterprise data platforms, and data warehousing methodologies, along with mandatory Azure https://jobeax.com/link/kAasWe1vkOLCgjzJ Responsibilities : - Design, build, and maintain enterprise-grade ETL/ELT data pipelines using Azure Data Factory (ADF) and Azure Databricks.- Architect and implement scalable data models (Data Modeling, Star Schema, Snowflake Schema) optimized for analytical processing.- Write high-performance SQL, Python, PySpark, and Spark SQL scripts for data transformation, processing, and analytics.- Design and maintain robust data warehousing solutions across Azure cloud infrastructure.- Implement CI/CD pipelines for data solutions to ensure seamless deployment and automated testing.- Collaborate with business intelligence teams to integrate data models with reporting tools (Power BI, DAX, SSRS, SSAS).- Ensure data governance, security, quality, and compliance across all data https://jobeax.com/link/lXelDJwchFiAqlII (Must-Have) : - Overall Experience : 6 to 10 years in Data Engineering and Cloud Data Architecture.- Core Technical Stack : Advanced proficiency in Azure Data Factory (ADF), Databricks, Apache Spark, Python, and SQL.- Data Architecture : Strong expertise in Data Modeling, enterprise Data Warehousing, and schema design.- Cloud Platform : In-depth knowledge of the Azure Data Platform.- Certifications : Mandatory active Azure Certifications (e.g., DP-203 : Data Engineering on Microsoft Azure or equivalent).Preferred Qualifications : - Hands-on experience with Microsoft Fabric.- Experience with Power BI, DAX, SSRS, and SSAS.- Exposure to Machine Learning principles and integrating ML workloads into data pipelines.- Familiarity with Data Governance frameworks and enterprise CI/CD processes.- Background or interest in Developer Advocacy, technical community engagement, or internal Data Engineering mentorship. (ref:hirist.tech)
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