Software Engineer III - Big Data Databricks, Python / Java

As a Software Engineer III at JPMorgan Chase within the Corporate Technology Sector, you provide expertise and engineering excellence as an integral part of an agile data engineering team. To enhance, build, and deliver a trusted market leading Global Know Your Customer (KYC) and Risk Assessment Data Platform in a secure, stable, and scalable way. Leverage your technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios.

Develops secure, high-quality production code for data-intensive applications and platforms Creates durable, reusable software frameworks and patterns that are leveraged across teams and functions 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. Advises cross-functional teams on technological matters within your domain of expertise 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 at scale. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale Expert in one or more programming languages, particularly Python and/or Java Deep knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering) 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. Experience in large-scale data processing, microservices, API design, Kafka, Redis, Memcached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal) Working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance Practical cloud-native experience (AWS, Azure, or GCP) Ability to present and effectively communicate with senior leaders and executives Preferred qualifications, capabilities, and skills Experience with modern data platforms such as Databricks or Snowflake Hands-on experience with Spark/PySpark and other big data processing technologies Expertise in open-source table formats and catalog services such as Apache Iceberg Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints such as AWS Bedrock, Azure OpenAI