Overview

We are seeking an experienced Senior Data Engineer with 7+ years in asset management or financial services to join our team. The ideal candidate will have expertise handling diverse datasets via batch files, APIs, and streaming from both internal and external sources.
Client:
Our client is a hedge fund sponsor that mainly manages pooled investment vehicles and typically invests in fixed income, private equity, rates, credit, and foreign exchange. The company operates offices in London, New York, and Hong Kong.
Project Overview:

Responsibilities:
  • Onboard new datasets and develop data models using Snowflake and DBT
  • Build and maintain data transformation pipelines
  • Design and manage data orchestration and ETL workflows with Azure Data Factory or Airflow
  • Optimize queries and apply data warehousing best practices for large and complex datasets
  • Collaborate with development teams using agile methodologies, DevOps, Git, and CI/CD pipelines
  • Support cloud-based services, especially Azure Functions, KeyVault, and LogicApps
  • Optionally develop APIs to serve data to internal or external stakeholders
Required Qualifications:
  • 7+ years as a Data Engineer in asset management or financial services
  • Expertise in Snowflake, DBT, and data pipeline orchestration tools (Azure Data Factory or Airflow)
  • Strong knowledge of SQL, Python, data modeling, and warehousing principles
  • Familiarity with DevOps practices including CI/CD and version control (Git)
  • Experience with Azure cloud services
Benefits:
  • 7+ years as a Data Engineer in asset management or financial services
  • Expertise in Snowflake, DBT, and data pipeline orchestration tools (Azure Data Factory or Airflow)
  • Strong knowledge of SQL, Python, data modeling, and warehousing principles
  • Familiarity with DevOps practices including CI/CD and version control (Git)
  • Experience with Azure cloud services
Note:
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