Senior Python Software Engineer III

As a Senior Associate Developer at JPMorganChase within the Corporate Technology Market Risk Management Development Organization, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art risk analytics platforms in a secure, stable, and scalable way. As a seasoned member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within data pipelines, applications, and systems, while collaborating with risk and business stakeholders to support the firm’s market risk management objectives.

Job Responsibilities

• Execute standard and advanced software solutions, including design, development, and technical troubleshooting of Python-based data pipelines and curated datasets for daily market risk analytics.
• Work shoulder to shoulder with business stakeholders, quantitative research analysts, and upstream/downstream technology teams, providing mentoring and guidance to junior engineers as needed.
• Write secure and high-quality code using Python and SQL, with limited guidance, applying best practices for data processing, automation, and operational reliability.
• Design, develop, code, and troubleshoot with consideration of upstream and downstream systems and technical implications, including integration with front-office risk management platforms.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• 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.
• Apply use of AI agents or AI-assisted engineering to improve productivity and reliability of developed products (optional plus).
• Apply technical troubleshooting to break down solutions and solve technical problems of moderate complexity, including production support and incident resolution.
• Gather, analyze, and draw conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development.
• Learn and apply system processes, methodologies, and skills for the development of secure, stable code and systems, including data quality controls (validation, reconciliation, lineage) and performance optimization.
• Add to team culture of diversity, equity, inclusion, and respect.

Required Qualifications, Capabilities, and Skills

• 3+ years of hands-on Python development for data processing and automation (e.g., pandas, packaging, testing).
• Demonstrable ability to code in SQL (at least one major dialect such as Oracle, SQL Server, PostgreSQL).
• Hands-on practical experience in system design, application development, testing, and operational stability, including building maintainable ETL/ELT pipelines.
• Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
• Experience across the whole Software Development Life Cycle, including agile methodologies such as CI/CD, application resiliency, and security.
• Proficiency with Git-based workflows and CI/CD; familiarity with production change management.
• Strong analytical and communication skills; collaborative approach with risk and business stakeholders.
• Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, etc.).

Preferred Qualifications, Capabilities, and Skills

• Experience with Databricks (Python notebooks, Delta Lake/Unity Catalog) and/or PySpark.
• Understanding of Big Data/Data Lake technologies (Spark, Hadoop, Databricks, etc.).
• Understanding of design patterns and clean coding principles.
• Familiarity with technical aspects of analytic applications and market risk concepts (e.g., sensitivities/Greeks, VaR, stress testing, limits, P&L decomposition).
• Exposure to agentic AI or AI-assisted engineering for testing, code generation, or data quality.
• Exposure to cloud data platforms (e.g., AWS, Azure), including object storage (S3/ADLS) and IAM basics.
• Familiarity with modern front-end technologies (optional plus).
• Exposure to Banking/Finance or Risk domains.