Software Engineer III - Data Engineering | Infrastructure Platforms
About The Position
As a Software Engineer III at JPMorganChase within the Infrastructure Platforms organization, you serve as a seasoned member of an agile team, designing and delivering trusted technology products in a secure, stable, and scalable way. You carry out critical technology solutions across technical areas and business functions in support of the firm’s objectives. You contribute throughout the delivery lifecycle to the design, development, testing, deployment, and improvement of secure, production-ready applications combining Java software engineering with Python-based AI/ML capabilities. The role addresses business problems, improves customer experiences, and increases operational efficiency in cloud and hybrid data environments. You also support the design and development of metrics reporting and dashboards that help Operations Management execute strategic objectives and ensure conformance with controls, policies, and procedures. JPMorganChase offers a competitive total rewards package, with base salary determined by role, experience, skill set, and location. Eligible roles may receive commission-based pay and/or discretionary incentive compensation. Benefits and programs, subject to eligibility, include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching. Additional compensation and benefits details are provided during the hiring process.
Requirements
- Formal training or certification in software engineering concepts and at least 3 years of applied experience.
- Practical experience in system design, application development across the SDLC, unit and integration testing, and operational stability for enterprise cloud-native applications.
- Understanding of software engineering fundamentals, APIs, source control, testing, debugging, and continuous integration and delivery practices.
- Experience developing, debugging, and maintaining code in a large corporate environment using modern programming languages, including Java and Python, and SQL.
- Experience with frameworks such as Spring Boot, Hibernate, and Envers.
- Experience with data-intensive and statistical applications such as Jupyter notebooks.
- Data engineering experience with Big Data, Data Mesh, Data Lake architecture, relational or graph databases, PL/SQL, data analytics, and dashboards such as Tableau or Qlik Sense.
- Experience with telemetry systems and tools such as Splunk or Elasticsearch.
- Solid understanding of Retrieval-Augmented Generation (RAG), agentic workflows, prompt engineering, and model development and testing.
- Hands-on experience with enterprise-authorized AI-assisted software development tools, with the ability to evaluate, validate, and refine generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations; ability to guide peers in safe and effective use.
- Exposure to cloud or hybrid platforms such as AWS and modern data or container platforms such as Databricks or Kubernetes.
Nice To Haves
- Bachelor’s degree in Computer Science with a specialization.
- Experience with data analytics.
- Experience with Oracle, MongoDB, or similar technologies.
- Experience deploying a vector database on services such as Google Kubernetes Engine (GKE) or Amazon Elastic Kubernetes Service (EKS).
Responsibilities
- Translate stakeholder and business requirements into technical solutions, prototypes, and delivery plans.
- Create secure, high-quality production code using Java and Python, and maintain algorithms that run synchronously with appropriate systems.
- Use SQL to analyze large, heterogeneous datasets, validate assumptions, generate insights, and measure solution impact.
- Contribute to scalable, resilient architectures and support deployment, monitoring, validation, troubleshooting, and iterative improvement.
- Automate operational processes and help eliminate recurring issues to improve platform stability and efficiency.
- Create unit and integration tests, participate in code reviews, and support continuous validation practices.
- Collaborate with product owners, operations, marketing, engineering, data, and other cross-functional teams to deliver end-to-end solutions aligned with enterprise standards.
- Produce technical documentation, reports, and presentations for technical and non-technical audiences.
- Support model and data governance by documenting solution design and providing technical input to risk, privacy, and controls assessments.
- Use enterprise-authorized AI coding assistance tools to improve code quality, delivery speed, and productivity; validate outputs through peer review, automated testing, and secure coding standards; and share learnings and reusable patterns.
- Apply knowledge of the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve automation outcomes.
Benefits
- Comprehensive health care coverage
- On-site health and wellness centers
- Retirement savings plan
- Backup childcare
- Tuition reimbursement
- Mental health support
- Financial coaching
- Competitive total rewards package
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
