Senior Big Data Engineer – Risk Analytics Leader

barclays; United States; On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k)

Incentive award

Job summary

Barclays is seeking a Lead Big Data Engineer – VP Risk Analytics in Whippany, NJ to scale enterprise risk platforms, drive regulatory and business transformation, strengthen engineering practices, and reduce delivery risk across technology. You will partner with Risk Managers, Quants, and Front Office stakeholders to deliver robust, scalable analytics solutions.

You will design and build data pipelines using Python/Java, Spark, SQL, Hadoop, and modern frameworks (FastAPI, Spring Boot, Flask,

Qualifications

• Experience designing and building scalable data platforms for financial services.
• Strong software engineering practices and coding discipline.
• Ability to build data pipelines and analytics workflows for risk management.

Responsibilities

• Design, develop, and maintain scalable software solutions for risk analytics and data platforms.
• Build and optimize data-intensive applications using Python, Java, Spark, SQL, and related tools.
• Implement robust testing and deployment practices to ensure quality and reliability.
• Develop end-to-end data transformation, enrichment, and workflow automation pipelines.
• Collaborate with Quantitative Analysts, Risk Managers, and Front Office stakeholders to deliver data-driven solutions.

Skills

Data platforms

Cross-team collaboration

OO programming

Risk analytics

Python

Java

Spark

SQL

Hadoop

Pandas

NumPy

Unix

PowerShell

PostgreSQL

MongoDB

PyTest

Tools

FastAPI

Spring Boot

Flask

Apache Airflow

HPC/Symphony Grid

AWS

Azure

Databricks

Snowflake

Job description

Barclays is seeking a Lead Big Data Engineer – VP Risk Analytics in Whippany, NJ to scale enterprise risk platforms, drive regulatory and business transformation, strengthen engineering practices, and reduce delivery risk across technology. You will partner with Risk Managers, Quants, and Front Office stakeholders to deliver robust, scalable analytics solutions.

You will design and build data pipelines using Python/Java, Spark, SQL, Hadoop, and modern frameworks (FastAPI, Spring Boot, Flask,