Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
HM
Hudson Manpower
Data Engineer Capital Markets
Career Insights for Data Engineer
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on New York data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$115,876 / year median in New York
+8% projected growth
Job Description
Job description Job DescriptionWe 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.
ResponsibilitiesDesign, 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.
Required Skills8-10 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.
The ideal candidate will have strong expertise in data engineering, data integration, data modeling, cloud data platforms, Fraud Screening, and Financial Crimes.
ResponsibilitiesDesign, 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.
Required Skills8-10 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.