Quant jobs / Citi

Senior Hands-on Technologist, Massive Scale Risk Analytics – Vice President

A senior data engineering role building the platform that stores and serves trade-level outputs from Citi's market risk engines, such as historical VaR and FRTB expected shortfall. It sits in market risk technology and serves front-office, quant and risk users.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build Spark pipelines that ingest billions of trade-level present value results
Write large aggregation jobs and tune them for speed
Load aggregated risk data into OLAP engines and build drill-down dashboards
Design data APIs, possibly with natural language query interfaces
Debug data and access issues with risk and quant stakeholders

What they ask for

Required

Apache Spark at scale
OLAP engines such as Pinot, Druid or Trino
Python, Java or Scala
Expert SQL
Data structures and algorithms
Degree in a quantitative or technical field

Preferred

Market risk, derivatives, VaR and stress testing knowledge
NLP applied to data access

Education: Degree in computer science, financial mathematics, financial engineering or a similar technical field
Experience: Senior hands-on engineer able to lead technical projects
Languages and tools: Python
Java
Scala
SQL
Apache Spark
Markets: multi-asset

How to prepare

Learn how historical VaR and expected shortfall are computed from trade-level PV vectors
Build a Spark job that aggregates synthetic scenario P&L by desk and book
Try loading data into an OLAP store such as Druid or Trino and query it interactively
Read an overview of the FRTB framework

What to study

Apply

Read the full posting on Citi’s site before applying: requirements, location and pay can change after we check them.

View the posting on Citi’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Citi and doesn’t handle applications.