Software Engineer – Data Platform (Risk & Regulatory
- Posted 20 April 2026
- LocationNew York
- Job type Contract
- Discipline Technology
Job description
Overview
We are seeking a Software Engineer to build and enhance scalable data platforms supporting risk and regulatory reporting within Capital Markets. This role focuses on engineering robust, high-performance systems that power intraday risk, end-of-day processes, and regulatory reporting (including FRTB), with strong emphasis on data integrity, lineage, and platform reliability.
Key Responsibilities
Platform & System Engineering
Design and develop scalable backend systems and services supporting risk and regulatory data workflows
Build reusable frameworks and components for data ingestion, processing, and validation
Develop APIs and services to expose risk data to downstream consumers
Data Platform Development
Engineer systems supporting:
Intraday risk data delivery (low latency)
End-of-day (EOD) batch processing
Regulatory reporting pipelines (FRTB)
Implement robust
data transformation and validation logic
Data Quality & Governance
Embed data quality controls, validation rules, and reconciliation logic into platform components
Ensure data lineage, traceability, and auditability across systems
Support and enforce data contracts for downstream systems
Performance & Scalability
Optimize systems for high-throughput, low-latency processing
Ensure resilience and fault tolerance in distributed environments
Collaboration
Work closely with Risk, Front Office, and Quant teams
to align on data requirements
Partner with Data Engineers and Architects on platform evolution
Required Experience
5–10+ years in software engineering, preferably in Capital Markets or financial services
Experience building distributed systems and data-intensive applications
Exposure to risk or regulatory data workflows (market risk, PnL, FRTB)
Technical Skills
Strong programming: Java, Scala, or Python
Experience with: Distributed systems design, event-driven architectures, Microservices / API development
Familiarity with data technologies:
Apache Spark
Kafka or similar messaging systems
Cloud experience: AWS, Azure, or GCP
