Data Engineering Associate

Join a team where your engineering skills shape technology powering millions of customers and businesses worldwide.

Join a team where your engineering skills directly shape the technology powering millions of customers and businesses worldwide. At JPMorganChase, we invest in our engineers, offering the tools, mentorship, and scale to help you grow from a strong individual contributor into a well-rounded technologist. As a Software Engineer III at JPMorganChase, you will contribute to the design, development, and delivery of scalable software solutions that support critical business operations. You will work within a collaborative engineering team, applying your technical expertise to solve complex problems while growing your skills across the full software development lifecycle. Your work will directly impact the reliability, performance, and innovation of systems used by clients and colleagues across the firm. Job responsibilities Design and develop high-quality, scalable software solutions aligned with business and technical requirements Contribute to all phases of the software development lifecycle, including design, coding, testing, and deployment Collaborate with cross-functional teams including product, architecture, and operations to deliver end-to-end solutions Identify and resolve technical issues, performing root cause analysis to prevent recurrence Write clean, maintainable code and participate in peer code reviews to uphold engineering standards Support continuous integration and continuous delivery pipelines to improve deployment frequency and reliability Contribute to technical documentation, ensuring clarity and accuracy for internal and external stakeholders Participate in agile ceremonies, providing input on sprint planning, estimation, and retrospectives 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 Strong data modeling expertise with proven experience modeling tables using ERwin, including normalization and dimensional modeling techniques Strong hands-on experience with Databricks as a data engineering platform, including building and optimizing ETL/ELT pipelines (performance tuning, partitioning, file sizing, and incremental loads) Strong proficiency in SQL, including advanced techniques such as joins, analytics and window functions, and query optimization Strong Oracle experience, including DDL/DML and schema design best practices, PL/SQL development (procedures, functions, and packages), and Oracle performance tuning (execution plans, indexes, partitioning, and statistics) Experience handling JSON and semi-structured data, including parsing, flattening, and schema evolution considerations Experience working with Databricks Genie Spaces and ThoughtSpot integration to Databricks Proficiency with Git-based workflows using Bitbucket and/or GitHub, with comfort working in IntelliJ IDEA or similar integrated development environments Strong problem-solving and debugging skills across ingestion, transformation, and serving layers 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 enabling or administering Unity Catalog, including catalog and schema design, permissions management, and lineage and metadata patterns Experience working in an agile or scrum delivery environment Exposure to containerization and orchestration technologies such as Docker or Kubernetes Familiarity with CI/CD tooling and DevOps practices Knowledge of financial services technology or regulated industry environments