Senior Quant Software Developer

We are seeking a Data Engineer with strong expertise in Python, PySpark, and SQL to design and maintain scalable solutions supporting financial markets, investment platforms, and portfolio management processes.

Responsibilities:

• Develop and maintain scalable solutions using Python, PySpark, and SQL.
• Design and implement data pipelines (ingestion, transformation, modelling, data quality checks, automation).
• Build and integrate APIs (REST, SOAP, gRPC) with authentication and authorization.
• Contribute to application architecture design, applying best practices and design patterns.
• Implement Test-Driven Development (TDD) and ensure high code quality.
• Support and enhance CI/CD pipelines and DevOps processes.
• Work with cloud platforms (AWS, Azure) and data platforms such as Databricks and Palantir Foundry.
• Develop UI components and dashboards using Dash, JavaScript, React.
• Integrate with market data and investment platforms.
• Support quantitative models and analytics (Monte Carlo simulations, pricing, risk, factor modelling).
• Contribute to portfolio management processes (asset allocation, rebalancing, attribution).
• Analyze complex datasets and deliver actionable insights for business and investment decisions.
• Gather and challenge business requirements, define solutions, and report on delivery progress.
• Collaborate within Agile teams, ensuring effective communication and alignment.
• Stay updated on emerging technologies and industry trends, proposing improvements.
• Balance short-term deliverables with long-term architectural goals.

Must Have:

• Advanced Python, medium PySpark, advanced SQL.
• Experience with Dash, JavaScript, React (preferred), OpenFin/FTC3 (preferred).
• Cloud experience: Azure (preferred), AWS (medium).
• Data platforms: Databricks (preferred), Palantir Foundry (medium).
• Strong background in TDD, CI/CD, DevOps.
• Application architecture design and development (design patterns).
• Data engineering expertise (ingestion, curation, modelling, automation, data quality checks).
• Advanced API knowledge (patterns, authorization, SOAP, REST, gRPC).
• Exposure to data science.
• Domain knowledge in financial markets, hedge funds, portfolio management, and quantitative processes.
• Experience sourcing and integrating data from core investment and market data platforms.

Nice to Have:

• Strong requirement gathering and reporting skills.
• Collaboration and Agile delivery mindset.
• Excellent problem-solving and interpersonal skills.
• Strong written and verbal communication.
• Ability to balance long-term architecture with short-term deliverables.