Data Engineering Associate

JPMorganChase is a financial institution that provides financial solutions to consumers, businesses, and institutional clients worldwide. The Data Engineering Associate will design, develop, and deliver scalable data and software solutions, contributing across the software development lifecycle. The role focuses on data modeling, Databricks ETL/ELT pipelines, SQL and Oracle development, automation, and reliable engineering practices.

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

Preferred

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

Unity Catalog Administration

Catalog

Schema Design

Permissions Management

Data Lineage

Metadata Patterns

Agile Delivery

Scrum Delivery

Docker

Kubernetes

CI/CD Tooling

DevOps Practices

Financial Services Technology

Regulated Industry Experience

Benefits

Eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.

Comprehensive health care coverage

On-site health and wellness centers

A retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Company

Retail and commercial banking, lending, and investment services

New York, New York, USA

https://www.chase.com/

Founded in 2000

10001+ employees

Qualifications

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

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

Required skills

Data Modeling, ERwin, Dimensional Modeling, Databricks, ETL/ELT Pipelines, SQL, Oracle, PL/SQL, JSON and Semi-Structured Data, Databricks Genie Spaces, ThoughtSpot, Git, Bitbucket/GitHub, IntelliJ IDEA, AI-Assisted Software Development, Responsible AI

Preferred skills

Experience working in an agile or scrum delivery environment, Familiarity with CI/CD tooling and DevOps practices

Experience

3+ years