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 career growth, and opportunities 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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