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We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorgan Chase within the  consumer and community banking- data technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Oversee all aspects of data strategy, governance, data risk management, reporting and analytics.
• Work with product owners, data owners and customers to evaluate data requirements and identify right technology solutions and implementation.
• Demonstrate practical experience in integrating AI technologies into business banking solutions, maintain a commitment to ethical and responsible AI use, and actively pursue ongoing learning in the rapidly evolving AI landscape.
• Design, develop, code, test, debug and deploy applications for scalable and extensible applications.
• Produce high quality code utilizing Test Driven Development techniques.
• Participate in retrospectives to drive continuous improvement within the feature team.
• Participating in code reviews and ensuring that all solutions are aligned to pre-defined architectural specifications.
• Implement Automation: Continuous Integration and Continuous Delivery.
• 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
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
• Manage Cloud Development and Deployment: Support development and deployment of applications into AWS Public clouds.

Required qualifications, capabilities, and skills.

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Advanced knowledge of architecture, design and business processes
• Expert-level implementation skills with Java, AWS, Database technologies, Python, Scala, Spark, Ab Initio or Informatica.
• Experience with the development and decomposition of complex SQL (RDMS Platforms)
• Experience with Data Warehousing concepts (including Star Schema).
• Practical experience in delivering projects in Data and Analytics, Big Data, Data Warehousing, Business Intelligence. Familiar with relevant technological solutions and industry best practices.
• Good understanding of data engineering challenges and proven experience with data platform engineering (batch and streaming, ingestion, storage, processing, management, integration, consumption).
• Aware of various Data & Analytics tools and techniques (e.g. Python, data mining, predictive analytics, machine learning, data modelling, etc.)
• Experience with one or more leading cloud providers (AWS/Azure/GCP)
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

Preferred qualifications, capabilities, and skills

• Ability to work fast and quickly ramp up on new technologies and strategies.
• Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals.
• Appreciation of Controls and Compliance processes for applications and data.  
• In depth understanding of data technologies and solutions is preferable.
• Drive Process improvements and implement process changes as necessary.
• Knowledge of industry-wide Big Data technology trends and best practices