We have an exciting opportunity for an experienced software engineer to shape the next generation of market risk reporting and analytics.
As a Software Engineer III in the Market Risk Data Visualization Team, you will provide hands-on technical leadership for data products that help risk professionals understand a large, complex, and fast-moving market risk environment. You will design and deliver high-quality analytical datasets, reporting pipelines, and visualization-ready views using PySpark, SQL, and modern cloud data platforms. You will work closely with risk managers, quantitative and data teams, product partners, and other engineers to turn complex business questions into clear, trusted, and useful reporting.
The team is advancing AI-enabled engineering practices to improve how it analyzes requirements, develops and tests pipelines, and delivers reporting capabilities. You will help establish effective patterns for this work, including sound engineering controls and human review, while remaining accountable for the quality, security, and correctness of production outcomes.
Job Responsibilities
- Design, build, and maintain production PySpark and SQL pipelines for market risk reporting and analytics.
- Transform complex source data into well-defined, reusable datasets and views for dashboards, reports, and analytical applications.
- Work with business partners and risk subject-matter experts to understand requirements, trace data needs, and deliver fit-for-purpose solutions.
- Apply data modeling, data quality, lineage, and governance practices so reporting outputs are consistent, traceable, and trusted.
- Develop secure, readable, and maintainable code; participate in design discussions, code reviews, and continuous improvement.
- Build and maintain automated tests and deployment workflows, and support monitoring and operational stability of data products.
- Investigate data discrepancies, performance bottlenecks, and production issues, and implement durable fixes.
- Use enterprise-authorized AI-assisted engineering tools to accelerate coding, testing, documentation, and troubleshooting while checking results for correctness, security, and performance.
- Explore practical uses of AI and automation in reporting and analysis, incorporating appropriate validation and human review.
Collaborate effectively with other engineers, business stakeholders, and platform teams to deliver work in an agile environment.
Required qualifications, capabilities, and skills
- Bachelor’s degree in computer science, data science, engineering, applied mathematics, or a related technical discipline, or equivalent practical experience.
- Strong professional experience developing and supporting production software or data engineering solutions.
- Strong Python and PySpark skills, with solid SQL and understanding of distributed processing concepts.
- Experience building data pipelines on a cloud data platform or lakehouse, working with large datasets and cloud object storage.
- Knowledge of data modeling, data quality, and the design of reliable datasets for analytics and reporting.
- Experience with software development fundamentals, including version control, testing, code review, CI/CD, and production support.
- Ability to analyze business and technical requirements and turn them into clear, maintainable implementations.
- Experience using approved AI-assisted development tools, with care to review and test generated output rather than relying on it without validation.
- Strong problem-solving, communication, and teamwork skills.
Interest in financial markets, market risk, or other complex data domains.
Preferred qualifications, capabilities, and skills
- Experience with Databricks, Apache Spark, Delta Lake, Unity Catalog, and Amazon Web Services.
- Experience preparing data for dashboards, visualization tools, regulatory reporting, or analytical applications.
- Familiarity with data governance, lineage, data observability, and data product practices.
- Exposure to LLMs, agentic AI, or automation techniques applied to software development or data workflows.
- Experience with APIs or services for accessing analytical data.
- Knowledge of market risk concepts such as sensitivities, Value at Risk, stress testing, or limits.
- Experience tuning Spark workloads and improving pipeline performance, reliability, or cost.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Bachelor's degree in computer science, data science, engineering, applied mathematics, or a related technical discipline, or equivalent practical experience
- Strong professional experience developing and supporting production software or data engineering solutions
- Strong Python and PySpark skills, with solid SQL and understanding of distributed processing concepts
- Experience building data pipelines on a cloud data platform or lakehouse, working with large datasets and cloud object storage
- Knowledge of data modeling, data quality, and reliable datasets for analytics and reporting
- Experience with version control, testing, code review, CI/CD, and production support
- Ability to analyze business and technical requirements and create clear, maintainable implementations
- Experience using approved AI-assisted development tools with output review and testing
- Strong problem-solving, communication, and teamwork skills
- Interest in financial markets, market risk, or complex data domains
- Experience with Databricks, Apache Spark, Delta Lake, Unity Catalog, and Amazon Web Services
- Experience preparing data for dashboards, visualization tools, regulatory reporting, or analytical applications
- Familiarity with data governance, lineage, data observability, and data product practices
- Exposure to LLMs, agentic AI, or automation techniques for software development or data workflows
- Experience with APIs or services for accessing analytical data
- Knowledge of market risk concepts such as sensitivities, Value at Risk, stress testing, or limits
- Experience tuning Spark workloads and improving pipeline performance, reliability, or cost
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
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Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
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Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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