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Data Engineer – Capital Markets

  • On-site
    • New York City, New York, United States
  • $50 - $55 per hour
  • Information Technology

Data Engineer with 8–10 yrs exp, strong Capital Markets, Fraud Screening & Financial Crimes domain knowledge, plus Python, Snowflake, SQL, ETL/ELT and cloud data engineering expertise.

Job description

Job Description

We are seeking a skilled Data Engineer with Capital Markets experience to design, build, and optimize scalable data pipelines supporting business intelligence, analytics, and AI initiatives.

The ideal candidate will have strong expertise in data engineering, data integration, data modeling, cloud data platforms, Fraud Screening, and Financial Crimes.

Responsibilities

  • Design, develop, and maintain robust ETL/ELT data pipelines.

  • Build and optimize large-scale data warehouses and data lakes.

  • Develop data models supporting reporting, analytics, and operational requirements.

  • Ensure data quality, integrity, governance, and security across platforms.

  • Work with structured and unstructured data from multiple sources.

  • Collaborate with business analysts, data scientists, and application teams.

  • Optimize SQL queries and data processing for performance and scalability.

  • Implement cloud-based data solutions using AWS, Azure, or GCP.

  • Automate data workflows, monitoring, and data quality processes using modern data engineering tools.

  • Support AI/ML initiatives by providing reliable and high-quality datasets.

  • Work with teams supporting Capital Markets, Fraud Screening, and Financial Crimes use cases.

Job requirements

Required Skills

  • 8–10 years of Data Engineering experience.

  • Strong Capital Markets domain experience.

  • Experience with Fraud Screening and Financial Crimes.

  • Strong Python skills.

  • Strong Snowflake experience.

  • Hands-on experience with ETL/ELT pipelines and data integration.

  • Strong SQL and data modeling experience.

  • Experience with cloud platforms such as AWS, Azure, or GCP.

  • Experience with data warehouses and data lakes.

  • Strong understanding of data quality, governance, and security.

  • Willingness to work onsite in New York, NY.

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