Senior Data Integration Engineer - CCR/EM Platform (Hybrid)

Synechron; New York (NY); Hybrid; USD 140,000 - 155,000; Full time

Benefits offered by this job

Competitive compensation

Hybrid work model

Global exposure

Training opportunities

Job summary

Synechron is seeking a senior data integration engineering leader in New York City to design, develop, and support scalable data solutions for Counterparty Credit Risk and Exposure Management platforms. You will lead data pipelines, ETL/ELT processes, and data governance in a global, hybrid environment.

The role requires deep Python/SQL expertise, Databricks/PySpark experience, and a strong background in financial services data analytics. Competitive compensation and global exposure are offered.

Qualifications

• 10+ years IT experience.
• Strong Python and SQL for data transformation and analytics.
• Hands-on with Databricks and PySpark for large-scale processing.
• Experience in data engineering, data integration, or enterprise data management in financial services.
• Cloud computing experience (Azure) and CI/CD tooling.

Responsibilities

• Design, develop, and maintain scalable data pipelines ingesting counterparty, trade, collateral, market, and exposure data.
• Build ETL/ELT solutions for structured and semi-structured data across batch and streaming environments.
• Utilize data platforms (data lakes, data warehouses, Databricks, Spark) for analytics and reporting.
• Integrate trading and derivatives data into CCR calculation, analytics, and reporting platforms.
• Lead modernization, automation, data quality, and governance initiatives across global teams.

Skills

Python

SQL

Databricks

PySpark

Cloud platforms

Data integration

Counterparty risk

Tools

Airflow

Job description

Synechron is seeking a senior data integration engineering leader in New York City to design, develop, and support scalable data solutions for Counterparty Credit Risk and Exposure Management platforms. You will lead data pipelines, ETL/ELT processes, and data governance in a global, hybrid environment.

The role requires deep Python/SQL expertise, Databricks/PySpark experience, and a strong background in financial services data analytics. Competitive compensation and global exposure are offered.