Location: Jersey City, NJ, United States

• Lead end-to-end architecture for Athena (Python), Databricks (PySpark/Delta Lake), and AWS-based valuation control platforms.
• Develop and enhance pricing, risk, IPV, valuation adjustment, and fair value reporting tools within Athena.
• Design, build, and optimize large-scale Databricks ETL and analytics pipelines for pricing, market, and P&L data.
• Architect and manage cloud-native AWS solutions, including infrastructure, security, automation, and modernization initiatives.
• Establish engineering best practices, code quality standards, CI/CD processes, testing frameworks, and production monitoring.
• Deliver automation and controls for independent price verification, valuation uncertainty detection, reconciliations, and regulatory compliance.
• Collaborate with valuation control, risk, finance, quants, and business stakeholders to define requirements and drive Agile delivery.
• Provide technical leadership, mentor engineering teams, oversee production support, and ensure scalable, auditable, and resilient solutions.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience 

• Extensive Python engineering experience; with hands-on platform experience and financial application engineering (derivatives pricing, risk management, trade booking, and quantitative analytics etc.).

• Strong Databricks / Apache Spark experience (PySpark, Delta Lake, performance tuning).

• Solid hands-on AWS experience across core services (S3, EC2, Lambda, IAM, and container/orchestration services), with an understanding of cloud security and cost management.

• Solid grasp of financial products, valuation/pricing concepts, and market data.

• Proven experience leading engineering teams and delivering in a controlled, regulated environment.

• Strong SQL, data modeling, and data-quality engineering skills.

• Excellent stakeholder management and the ability to bridge business and technical domains.

Preferred Qualifications

• Knowledge of IPV, prudent valuation, XVA, or fair-value reserve methodologies.
• Experience with reactive/streaming computation and real-time dashboards.
• Infrastructure-as-code (Terraform/CloudFormation), CI/CD, and modern DevOps practices on AWS.
• AWS certification (e.g., Solutions Architect, Developer, or Data Engineer Associate/Professional).