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Python Data Engineer (Azure), Investment Management

  • Ню Йорк
Гореща позицияСреден екип (10-20 души)

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Client

Our client is a US-based investment management company listed in the Fortune Global 500. It offers insurance, investment management, and other financial products and services to retail and institutional clients across the United States and over 40 other countries.

Наемаме ви в компанията, не в проект

Position overview

We are seeking a Python Data Engineer (Azure) to join our team. In this role, you will be responsible for creating Microsoft Fabric pipelines and organizing ETL/ELT processes supporting a leading investment management company.

The estimated salary range for this position is 100,000 to 125,000 USD per year.

The role is hybrid and requires the ability to visit the client's office in Newark, NJ minimum 3 times per week.

Responsibilities

  • Develop, deploy, and maintain data pipelines using Azure Data Factory and other Azure data services to support business intelligence and analytics needs
  • Design, implement, and optimize SQL queries and stored procedures to ensure high performance and data accuracy
  • Write efficient, scalable Python code for data processing, transformation, and analysis tasks
  • Build and maintain Spark and PySpark workflows for large-scale data processing in distributed environments
  • Collaborate with data engineers, data scientists, and business stakeholders to define data requirements and design data models
  • Ensure data security and governance by implementing best practices using Azure Security services and managing access controls in Azure Portal
  • Monitor, troubleshoot, and optimize the performance of data infrastructure and workflows
  • Work with relational and non-relational databases such as MS SQL, PostgreSQL, and Redshift to manage and analyze data
  • Support the creation of data visualizations and reports using PowerBI to provide actionable insights
  • Stay updated with the latest technologies in data engineering and cloud services; recommend and implement improvements

Requirements

  • 5+ years of expert-level SQL experience
  • 3+ years of strong hands-on Python engineering experience
  • 2+ years of practical experience with Azure data services, especially Azure Data Factory or Microsoft Fabric
  • 2 years of practical experience with Apache Spark, especially PySpark
  • Experience working with Azure Security services and managing via Azure Portal
  • Knowledge and practical experience in data warehousing, data governance, and data management

Nice to have

  • Practical experience with MS SQL
  • Practical experience with PostgreSQL
  • Practical experience with Amazon Redshift
  • Experience with Java and Scala
  • Experience with PowerBI

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