Job Overview:

Our client is a renowned global banking and financial services organization delivering enterprise-scale cloud, data, and digital transformation programs. The organization offers a collaborative environment, modern technology stack, long-term growth opportunities, and prospects to work on high-impact platforms supporting millions of users worldwide. We are looking for a Cloud Data Engineer with strong Microsoft Azure experience to design, build, and maintain scalable enterprise data platforms.

Detailed Job Description:

This role includes developing cloud-native data pipelines, API integrations, and high-performance data solutions supporting advanced analytics and business intelligence. You will build ETL/ELT workflows, integrate APIs, and develop high-performance data solutions that power advanced analytics, reporting, and business intelligence across a mission-critical enterprise cloud and data transformation program.

Key Responsibilities:
Design, build, and maintain scalable data pipelines using Azure Data Factory, Azure Synapse, and Databricks




Develop ETL/ELT processes to ingest, transform, and load data from diverse enterprise sources
Build and integrate REST APIs for data exchange between systems and platforms
Write productive, production-grade code in Python and Spark/PySpark for large-scale data processing
Optimize data storage and retrieval using Azure Data Lake and related cloud-native services
Implement and manage CI/CD pipelines using Azure DevOps for automated deployment of data solutions
Collaborate with Analytical Engineers, Solution Architects, and BI teams to deliver end-to-end data solutions
Monitor, troubleshoot, and optimize data pipeline performance, reliability, and scalability
Apply cloud security best practices to protect sensitive enterprise and financial data
Contribute to enterprise data warehousing strategy and analytics engineering initiatives

Mandatory Technical Skills:

Microsoft Azure, Azure Data Facto

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