Overview

The Data Engineer will develop scalable and efficient data model architectures that integrate both current operational and historical data, ensuring high data quality, consistency, and optimal query performance across real-time and historical datasets.
Client:
Our client is a global value-based asset management firm headquartered in the US. The client serves individual and institutional investors through five no-load mutual funds and eleven separate account strategies.
Project Overview:

Responsibilities:
  • Design and implement ETL pipelines using Azure Data Factory following ETL best practices and design patterns.
  • Work with MS SQL Server to optimize database performance and data modeling.
  • Manage and maintain CI/CD pipelines for seamless integration and deployment.
  • Collaborate with data engineers, analysts, and stakeholders to ensure data quality and architecture scalability.
Nice To Have:
  • Strong problem-solving skills and attention to detail.
  • Effective communication and collaboration skills within a cross-functional team.
  • Ability to work independently and manage multiple priorities.
Required Qualifications:
  • Strong proficiency with Azure, specifically Azure Data Factory (ADF).
  • Expertise in MS SQL Server including performance tuning and query optimization.
  • Solid understanding of ETL best practices and design patterns.
  • Experience working with GitHub for version control and collaboration.
  • Hands-on experience with CI/CD pipeline creation and maintenance.
  • Knowledge of cloud data architectures and data modeling best practices.
Note:

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