DE&A - Core - Big Data Engineer- Hadoop Ecosystem

Key Responsibilities

1. Quantitative Model Design & Development

• Architect and develop financial models for pricing, risk, and trading strategies

• Design frameworks for derivatives pricing, portfolio optimization, and risk analytics

• Ensure models are scalable, reusable, and production-ready

2. Architecture & Platform Development

• Define and drive end-to-end architecture for quant platforms

• Build high-performance systems using Python/C++/Java

• Integrate models with data pipelines, APIs, and cloud platforms (AWS/Azure/GCP)

3. Risk & Analytics Solutions

• Develop solutions for market risk, credit risk, liquidity risk, and PnL attribution

• Architect real-time and batch analytics systems for large datasets

• Ensure compliance with regulatory frameworks (Basel III, IFRS9, etc.)

4. Collaboration & Stakeholder Management

• Work closely with quants, traders, risk teams, and data engineers

• Translate business requirements into technical and analytical solutions

• Provide technical leadership and mentoring to quant developers

5. Performance Optimization & Governance

• Optimize model performance and computational efficiency

• Implement validation frameworks, backtesting, and model governance

• Ensure code quality, maintainability, and version control

Key Competencies

• Strong analytical and problem-solving skills

• Ability to simplify complex financial concepts

• Leadership and stakeholder management

• High attention to detail and accuracy

Typical Use Cases Delivered

• Pricing engines for derivatives

• Risk analytics platforms (VaR dashboards, stress testing tools)

• Algorithmic trading systems

• Portfolio optimization frameworks

Mandatory Skills

Quantitative & Financial Expertise

• Strong knowledge of:

• Derivatives pricing (Black-Scholes, Monte Carlo, etc.)

• Fixed income, equities, FX, and structured products

• Risk frameworks (VaR, CVA, stress testing)

Technical Skills

• Programming: Python (Must), C++/Java (Preferred)

• Libraries: NumPy, Pandas, SciPy, TensorFlow (good to have)

• Experience with big data tools (Spark, Hadoop)

• Database knowledge: SQL, NoSQL

Data & Architecture

• Experience designing data-driven architectures and APIs

• Hands-on with cloud platforms (AWS/Azure/GCP)

• Familiar with microservices architecture

Good-to-Have Skills

• Exposure to AI/ML in quantitative finance

• Knowledge of Databricks, Snowflake, or similar platforms

• Experience with real-time streaming (Kafka, Flink)

• Certification like FRM, CFA, CQF

Experience & Qualifications

• Education: Bachelor s/Master s/PhD in Mathematics, Finance, Engineering, or related field

• Experience: 8 15 years in quantitative development/architecture

• Strong experience in financial services (Banking, Capital Markets, Hedge Funds)