Software Engineer III - Python, Spark/PySpark, Databricks, SQL

Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III - Python, Spark/PySpark, Databricks, SQL at JPMorgan Chase within the Commercial & Investment Bank, you'll 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 Develop workflows and ELT data pipelines using Python, Spark/PySpark, and Databricks Build, test, and maintain scalable data pipelines and data architectures that support enterprise analytics use cases Apply data engineering best practices for performance optimization, reliability, and maintainability and Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Support implementation of data security, governance, and entitlements frameworks to protect enterprise data Use SQL extensively and work with both relational and NoSQL data stores Partner with stakeholders to understand data requirements and translate them into production-ready solutions Apply SDLC practices including CI/CD, testing, and operational monitoring to ensure pipeline stability Contribute to reusable frameworks and standards to accelerate onboarding and pipeline delivery Identify data issues, anomalies, and optimization opportunities to improve data quality and performance 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. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on experience with Databricks, Spark/PySpark, Python, and SQL Experience developing and maintaining data pipelines and data processing systems Understanding of the data lifecycle, including ingestion, transformation, storage, and consumption Knowledge of cloud platforms (AWS) and distributed data processing Experience with SDLC practices including CI/CD, testing, and deployment Strong problem-solving skills and ability to troubleshoot data and pipeline issues Ability to collaborate effectively within agile teams and across stakeholders 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. Preferred qualifications, capabilities, and skills Experience with Databricks lake house, Delta Lake, and medallion architecture Exposure to data quality, observability, and metadata management tools Experience supporting analytics, reporting, or AI/ML workloads Familiarity with modern front-end technologies Exposure to cloud technologies