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Software Engineer - Market Risk Technology

Job in New York, New York County, New York, 10261, USA
Listing for: Capgemini
Full Time position
Listed on 2026-10-03
Job specializations:
  • Software Development
    Data Engineering, AI Engineer (Applied/Software), Software Engineer, Python
Salary/Wage Range or Industry Benchmark: 103330 - 128656 USD Yearly USD 103330.00 128656.00 YEAR
Job Description & How to Apply Below
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Job Location Job is located in NJ - Onsite Hybrid Your Role Your Role and Impact As a Senior Technologist, you will be at the heart of the action, designing the systems that power our most sophisticated risk-based calculations. You will take the raw, trade-level Present Value (PV) outputs from our Historical VaR and FRTB Expected Shortfall engines and transform them into a strategic data asset.

Your impact will be immediate and far-reaching. You will build the data pipelines that handle immense volumes, create intelligent APIs that democratize data access, and leverage cutting-edge OLAP and NLP technologies to provide unparalleled drill-down and analytical capabilities. You will be the go-to expert who empowers senior stakeholders in the Markets and Risk organizations to make faster, smarter decisions.

Key Responsibilities Architect and build robust, scalable data pipelines to ingest and process billions of trade-level PV calculations from various stress engines.

Develop and optimize large-scale aggregation jobs using Apache Spark, ensuring high performance and efficiency.

Design and deliver a suite of 'intelligent data APIs' that provide flexible, on-demand access to both aggregated and non-aggregated risk data for teams across the firm.

Integrate Natural Language Processing (NLP) capabilities to create intuitive, query-based interfaces for data exploration, lowering the barrier to entry for complex analytics.

Load and model massive aggregated datasets into high-performance OLAP engines like Apache Pinot, Apache Druid, and Trino.

Build powerful, interactive analytical tools and dashboards on top of the OLAP layer, providing summary views and lightning-fast drill-down capabilities.

Partner directly with senior stakeholders in the Front Office, Quantitative teams, and Risk Management to understand their analytical needs and deliver innovative solutions.

What We're Looking ForA true passion for data, analytics, and solving complex problems at massive scale.

A degree in a quantitative or technical field such as Computer Science, Financial Mathematics, or Financial Engineering.

Expert-level, hands-on experience with big data technologies, particularly Apache Spark.

Proven experience with high-performance OLAP databases such as Apache Pinot, Apache Druid, or Trino.

Strong programming skills in Python, Java and/or Scala, and expert-level SQL.Strong background in fundamental computer science concepts, including data structures and algorithms.

A mindset for 'AI-first' development, constantly looking for ways to embed intelligence into systems.

Experience or a strong interest in applying Natural Language Processing (NLP) to data access and analytics.

The base compensation range for this role in the posted location is: 103330 to 128656

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may…
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