The Role: Quantitative Engineer / QA Lead, Microservices Transformation The Team: Establish FRA Prototype Team & Delivery Approach A full-scale microservices transformation of the S&P; Globals Financial Risk Analytics product, pre-AI, was expected to require a large pool of technology roles across architecture, engineering, platform, security, operations, and delivery.

For the initial FRA prototype transformation, we want to stand up a lean, generative-AI enabled transformation squad with a focused team structure sized to deliver a validated microservices foundation.

The objective is to establish an agile technology transformation group to design and deliver a commercially aligned, targeted microservices architecture for the FRA platform, prioritizing measurable business outcomes and rapid learnings.

Responsibilities and Impact:

- Lead the quality assurance of transformed financial services by establishing rigorous automated testing frameworks that ensure correctness, regulatory compliance, and data integrity.
- Develop comprehensive integration, regression, and scenario testing to validate service outputs, pricing models, algorithms, and statistical results, safeguarding analytical accuracy.
- Drive regulatory compliance by ensuring auditability, supporting model governance, and embedding controls that meet financial industry standards and controls frameworks.
- Design and execute stress testing and risk scenarios to identify vulnerabilities, ensure resilience, and maintain confidence in critical financial calculations and models.
- Collaborate closely with risk, compliance, and audit teams to embed validation processes that support transparency, traceability, and regulatory reporting requirements.
- Join a transformation journey where your expertise ensures that innovative financial services are reliable, compliant,



and built on a foundation of rigorous quality assurance.

What We’re Looking For: Key qualifications for the job

- Positive to have CFA/FCM qualification with a strong quantitative analysis capability
- Python / SQL
- Automated testing framework design (with experience in generative-AI development)
- Financial modelling

Key soft skills

- Attention to detail and precision — Ensuring regulatory compliance, data integrity, and model accuracy requires meticulousness and a thorough approach.
- Strong analytical and critical thinking — Ability to interpret complex financial models, identify risks, and validate outputs effectively.
- Effective communication and collaboration — Working with product, compliance, audit, and technical teams to ensure transparency, traceability, and regulatory adherence.
- Resilience and problem-solving under pressure — Handling high-stakes validation and testing scenarios, especially during audits or regulatory reviews, with calm and confidence.

Additional key qualifications for the job

- Capital markets
- Risk analytics
- Investment systems
- Model validation

Additional soft skills

- Industry acumen and contextual understanding — Deep knowledge of capital markets, risk analytics, and investment systems to interpret complex models and ensure relevance.
- Critical thinking and judgment — Ability to assess model validity, identify potential biases, and evaluate risk implications with sound judgment.
- Effective stakeholder engagement — Communicating complex validation results clearly to non-technical stakeholders, including front-office, risk managers, and regulators.
- Adaptability and continuous learning — Staying current with evolving financial regulations, market practices, and modeling techniques to ensure ongoing compliance and accuracy.

📌 Quality Engineering Lead (Mumbai)
🏢 Su0026P Global Market Intelligence
📍 Mumbai