Risk Data Pipeline

About the Role

We are seeking a highly skilled

Risk Data Pipeline Engineer

to design, build, and maintain scalable data pipelines supporting

risk management, market data, and trading analytics . The ideal candidate will have strong programming expertise, hands-on experience with data engineering workflows, and a deep understanding of financial instruments and risk concepts.

You’ll work closely with

Risk, Quant, and Technology teams

to ensure accurate, real-time data flow for risk computations, exposure monitoring, and regulatory reporting.

Key Responsibilities

Design, develop, and maintain

end-to-end data pipelines

for risk and P&L systems.

Integrate and transform data from multiple sources —

trading systems, market data feeds, position data, reference data , etc.

Ensure

data quality, consistency, and timeliness

across all risk data layers.

Collaborate with

Risk, Quant, and DevOps teams

to support risk calculations and analytics.

Build

automated validation, monitoring, and alerting

systems for critical data flows.

Optimize ETL workflows and improve

data processing efficiency and scalability .

Contribute to the design and implementation of

data models and schemas

for risk systems.

Troubleshoot data and performance issues in production environments.

Required Skills & Experience

Strong programming skills in

Python

and

SQL

(experience with

Pandas ,

PySpark , or

Airflow

is a plus).

Hands-on experience with

data pipeline tools

(e.g.,

Airflow ,

Luigi ,

Kafka ,

AWS Glue , or similar).

Strong understanding of

database systems

— relational (PostgreSQL, MySQL, Oracle) and / or NoSQL (MongoDB, Redis).

Exposure to

risk management concepts

— VaR, exposure, sensitivities, stress testing, etc.

Familiarity with

financial data types

— trades, positions, reference data, pricing data, and market feeds.

Experience working in

Unix / Linux environments

with scripting knowledge (Shell, Bash).

Strong analytical and problem-solving skills, attention to detail, and ownership mindset.

Preferred / Nice-to-Have Skills

Knowledge of

cloud platforms

(AWS, GCP, or Azure) and

data lake / data warehouse

architectures.

Familiarity with

quant / risk systems

or

risk engines

(Murex, Calypso, proprietary risk systems).

Understanding of

fixed income, derivatives, and equities .

Experience in

distributed data processing

(Spark, Hadoop).

Prior experience in

hedge funds, investment banks, or fintech firms

preferred.

Education

Bachelor’s or Master’s degree in

Computer Science, Engineering, Mathematics, or a related discipline .

Strong academic background with exposure to

data structures, algorithms, and statistics .

Why Join Us

Work with global

Risk, Quant, and Technology

teams on mission-critical systems.

Be part of a

high-performance engineering culture

driving real-time financial insights.

Opportunity to shape and optimize

data-driven risk infrastructure

in a dynamic financial environment.