Lead Software Engineer (VP) - Valuation Control Group Technology

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 280,000; Full time

Job summary

JPMorgan Chase & Co. in Jersey City invites a Lead Software Engineer (VP) to join the Valuation Control Group Technology team.

You will be a core technical contributor, shaping architecture for Athena, Databricks, and AWS-based valuation platforms while delivering trusted, scalable software in a regulated environment. You will lead engineering teams, mentor engineers, and collaborate with risk, finance, quants, and business partners to define requirements, drive Agile delivery, and implement

Qualifications

• 5+ years of applied software engineering experience.
• Extensive Python engineering with finance domain exposure.
• Strong Databricks / Apache Spark (PySpark, Delta Lake) experience.
• Hands-on AWS across S3, EC2, Lambda, IAM; cloud security awareness.
• Solid knowledge of financial products, valuation concepts and market data.
• Experience leading engineering teams in regulated environments.
• Strong SQL, data modeling, and data-quality engineering.

Responsibilities

• 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.
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation.

Skills

Python

Databricks / Apache Spark

AWS

SQL

Stakeholder management

Leadership

Data modeling

Financial domain knowledge

Education

Formal training or certification in software engineering concepts

Tools

Terraform

CloudFormation

CI/CD tooling

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer (VP) - Valuation Control Group Technology at JPMorganChase within the Valuation Control Group Technology Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.

As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Responsibilities

• 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).