Senior Data Integration Engineer - New York, NY - DIE26-06669

NavitasPartners•New York, NY

1d•Onsite

About The Position

We are seeking a Senior Data Integration Engineer to design, develop, and support scalable data integration solutions for Counterparty Credit Risk (CCR) platforms. The ideal candidate will have strong experience with Python, SQL, Databricks, and PySpark, and a proven background in risk data, ETL development, and financial services.

Requirements

10+ years of experience in Python development and advanced SQL programming.
5+ years of experience in Data Engineering, Data Integration, or Enterprise Data Management within Financial Services.
3+ years supporting Risk, Exposure Management, or Counterparty Credit Risk platforms in a senior technical leadership capacity.
3+ years of hands-on experience with Databricks and PySpark for large-scale data processing and ETL development.
Experience working within globally distributed support and delivery models.
Must be eligible for Security Clearance.
Only candidates with 10+ years of experience will be considered.

Nice To Haves

Strong experience with Python, SQL, PySpark, Databricks, and Snowflake.
Experience building ETL/ELT pipelines and large-scale data integration solutions.
Knowledge of Counterparty Credit Risk (CCR), including EPE, PFE, EAD, collateral, and exposure management.
Experience with Azure Cloud, Data Lakes, ADF, and distributed data processing frameworks.
Familiarity with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps.
Experience working in Agile environments using JIRA and Confluence.

Responsibilities

Design, develop, and maintain scalable data pipelines for counterparty, trade, collateral, and market data integration.
Build and support ETL/ELT solutions using Python, PySpark, Databricks, and SQL.
Integrate risk and trading data into Counterparty Credit Risk (CCR) calculation and reporting platforms.
Partner with Risk, Business Analysts, and Technology teams to gather requirements and deliver data solutions.
Ensure data quality, reconciliation, monitoring, and governance across risk data platforms.
Support exposure analytics, including EPE, PFE, EAD, stress testing, and regulatory reporting.
Investigate and resolve data and production issues through root cause analysis and permanent fixes.
Implement automation, monitoring, and operational improvements to enhance platform reliability.
Lead platform enhancements, migrations, and strategic data initiatives.
Maintain technical documentation and support audit and regulatory data requests.