We are looking for a Senior Financial Risk Engineer to own and evolve the core calculation engine behind our ALM and regulatory platform.
This is not a generic backend role. Your primary responsibility is the design and implementation of financial and risk calculations - interest rate risk (IRRBB), liquidity (LCR), stable funding (NSFR), economic value metrics, and balance sheet simulations - within a distributed, cloud-ready architecture.
You will sit at the intersection of:
Quantitative / functional risk expertise (ALM, liquidity, regulatory capital), and
Robust software engineering (Java, distributed compute, performance, correctness).
If you enjoy:
Translating ALM, treasury, and Basel rules into executable models,
Designing cash-flow engines and scenario frameworks,
If numerical robustness and explainability of risk metrics at scale, then this role is designed for you.
Lead the design and implementation of core financial/risk models in Java within the RiskPro calculation engine.
Work with risk, treasury, and regulatory SMEs to:
Validate calculation approaches against ALM desk practice and regulatory expectations
Design scenario libraries and stress testing frameworks (rate shocks, liquidity stresses, balance sheet strategies)
Implement unit, scenario, and regression test suites:
Golden datasets with known outputs for IRRBB, LCR, NSFR, FTP, etc.
Non-regression tests when regulatory rules or models are updated
Collaborate closely with:
Platform engineers on deployment, performance, and observability (Kubernetes, Ignite, OTEL)
RRH teams to ensure consistent behaviour of the single-calculation / enrichment loop
Contribute to and review technical specifications and design documents for calculation changes.
Provide technical and functional mentorship to other developers in the squad on financial calculations.
Several years working hands-on with ALM / Treasury / Risk calculation engines in banking or vendor software, covering at least some of:
IRRBB (NII, EVE, gap/duration analysis)
Liquidity risk: cash flow engines, LCR and NSFR calculation
FTP and balance sheet optimisation, behaviour modelling (prepayment, decay)
Deep familiarity with cash-flow-based modelling:
Building/maintaining engines that project interest and principal flows over time
Handling behavioural vs contractual views and multiple scenario overlays
Strong understanding of banking products and their risk characteristics:
Retail and wholesale deposits, term deposits, loans/mortgages, securities (bonds), off-balance sheet items, derivatives used for hedging
Technical / Engineering
Strong software engineering skills in Java (preferably Java 11+):
Solid OO and functional design, collections, concurrency
Implementing performant algorithms for large-scale data processing
Experience building calculation services that run as part of:
Batch job frameworks, grid/distributed compute, or microservice-based calculation engines
Competence with relational databases (e.g., MS SQL Server, Oracle, AzureSQL):
Understanding of schemas that support risk / ALM data
Comfortable with efficient querying and aggregation patterns
Good understanding of:
RESTful APIs and data contracts (JSON, OpenAPI)
Working in a containerized environment (Docker, Kubernetes) with a basic understanding of how services scale and communicate
Experience with:
Apache Ignite or other distributed in-memory grids / caches
WebSocket-based result streaming or high-volume data export APIs
OLAP or multidimensional analytics (ActiveViam Atoti, or similar)
Prior work on:
Unified risk and regulatory platforms where internal risk numbers must reconcile to regulatory filings
Implementing or validating models against EBA / ECB / Basel III / CRR technical standards
Familiarity with:
OpenTelemetry (metrics, traces), correlation IDs, and traceability patterns for complex calculations
Dev practices around model governance (model change logs, validation, challenger models)
You think like both a quant and a software engineer: you care that the numbers are right, explainable, and repeatable, and that the code is robust and maintainable.
You are comfortable debating behavioural assumptions, discount curves, and regulatory interpretations, then turning decisions into code and tests.
You enjoy working in a cross-functional squad with product, architects, and domain experts, owning problems from idea to production.
You are motivated by seeing how your calculations directly influence ALCO decisions, regulatory headroom, and capital efficiency for our clients.
Regnology ist ein international führender Anbieter für innovative Lösungen im Bereich Regulatory, Risk und Supervisory Technology (RegTech/RiskTech/SupTech), für AEOI und Steuerreporting sowie für Services für das aufsichtsrechtliche Meldewesen entlang der regulatorischen Wertschöpfungskette. Regnology ist seit 25 Jahren ein Partner für Banken und Regulierungsbehörden. Bis Ende 2020 war das Unternehmen Teil der BearingPoint-Gruppe und firmierte unter dem Namen BearingPoint RegTech. Seit dem Verkauf des RegTech-Geschäfts an das Private-Equity-Unternehmen Nordic Capital ist das Unternehmen unabhängig. Im Juni 2021 hat sich das Unternehmen mit Vizor Software zusammengeschlossen und kürzlich den Namen in Regnology geändert. Insgesamt nutzen mehr als 7.000 Firmen, darunter Banken, Versicherungen und Finanzdienstleister, Reporting-Lösungen von Regnology. Gleichzeitig setzen mehr als 50 Aufsichtsbehörden und Steuerbehörden auf fünf Kontinenten die SupTech-Lösungen des Unternehmens ein, um Daten von 34.000 Firmen in 60 Ländern zu erfassen und zu analysieren. Regnology beschäftigt insgesamt über 770 Mitarbeiter an 17 Standorten in 12 Ländern.
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