Software Engineer III - Databricks

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 JPMorganChase within the Commercial & Investment Bank - Digital & Platforms Services team, 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.

You will help build and support enterprise data products and data platforms that power analytics, reporting, operational, and AI-driven solutions. Working alongside senior engineers, architects, and product teams, you will develop scalable data pipelines, contribute to data product development, and grow your expertise in modern Data Engineering practices.

Job Responsibilities

Design, develop, test, and support data pipelines and data products using modern Data Engineering practices.

Build and maintain scalable data ingestion, transformation, and integration processes on Databricks and related platform technologies.

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.

Implement data quality, validation, monitoring, and observability controls to ensure reliable and trusted data.

Contribute to the development of analytical, operational, reporting, and AI-enabled data solutions.

Collaborate with engineers, architects, product owners, and business stakeholders to understand requirements and deliver data solutions.

Troubleshoot data pipeline issues, support production environments, and participate in operational support activities.

Apply established engineering standards, design patterns, and best practices while continuously improving development skills.

Participate in code reviews, testing, documentation, and release activities to ensure high-quality delivery.

Identify opportunities to improve data quality, platform efficiency, automation, and engineering productivity.

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and 3+ years applied experience

Experience working with Databricks and distributed data processing technologies.

Strong programming skills and understanding of Data Engineering fundamentals.

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.

Familiarity with data architecture concepts, data modeling, and data product principles.

Experience building and supporting batch and/or real-time data pipelines.

Strong analytical and problem-solving skills with the ability to troubleshoot technical issues independently.

Understanding of software development lifecycle practices, testing, version control, and CI/CD concepts.

Strong communication and collaboration skills with the ability to work effectively in cross-functional teams.

Preferred Qualifications

• Experience working with modern enterprise data platforms and cloud-native data architectures.
• Experience supporting real-time, analytical, or AI/ML-oriented data use cases.
• Experience delivering data solutions within financial services or another highly regulated environment.
• Relevant Databricks, cloud, or Data Engineering certification.