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Data Engineer (Cloud ETL & Data Platforms) #3583285
Jersey City, NJ
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Be Part Of A High-Performing Team:

Join a leading global financial institution recognized for its strong presence in corporate banking, investment banking, and financial services innovation. The technology division plays a critical role in driving data transformation initiatives across the Americas, supporting enterprise-scale systems and regulatory environments. This team operates in a fast-paced, highly collaborative environment focused on modernizing data infrastructure, improving data accessibility, and enabling advanced analytics across the organization.

What's In Store For You:

  • Engagement: W2 only (no C2C/1099)
  • Opportunity to work on large-scale enterprise data platforms within a global financial services environment
  • Exposure to modern cloud-based data engineering tools and frameworks
  • Long-term contract with potential for extension based on performance and business needs

How You Will Make An Impact:

  • Design, build, and maintain scalable ETL pipelines to support enterprise data initiatives
  • Develop and optimize data workflows for ingestion, transformation, and storage
  • Ensure data quality, integrity, and consistency across multiple data sources
  • Collaborate with cross-functional teams including analytics, infrastructure, and business stakeholders
  • Enhance performance and efficiency of data systems and storage solutions
  • Support cloud-based data platform initiatives and modernization efforts

Are you an experienced Data Engineer ready to make an impact in cloud-based data platforms?

  • 5–7 years of experience in data engineering, ETL development, or data platform engineering
  • Strong proficiency in Python and SQL for data processing and pipeline development
  • Hands-on experience with cloud data tools such as AWS Glue, Azure Data Factory, or similar platforms
  • Experience working with large-scale data environments and optimizing data workflows
  • Solid understanding of data modeling, data warehousing, and data quality best practices
  • Ability to troubleshoot data issues and implement scalable solutions
  • Strong communication skills and ability to work in a hybrid team environment
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