Software Engineer II - Big Data

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