Software Engineer III: Data Engineer

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Engineer III at JPMorganChase within the CCB Connected Commerce - Banking Payments, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way.

You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities



* Supports review of controls to ensure sufficient protection of enterprise data


* Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems .


* Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems.


* Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.


* Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.


* Proactively identifies hidden problems, patterns in data, and uses these insights to drive improvements to coding hygiene and system architecture.


* Contributes to software engineering communities of practice and events that explore new and emerging technologies


* Updates logical or physical data models based on new use cases


* Frequently uses SQL and understands NoSQL databases and their niche in the marketplace

Required qualifications, capabilities, and skills



* Formal training or certification on Software Engineering concepts and 3+ years applied experience


* Working understanding of NoSQL databases with Advanced at SQL (e.g., joins and aggregations)


* Experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis


* Experience in ETL process/Advance concepts


* Hands-on practical experience in system design, application development, testing, and operational stability


* Experience in AWS, design, implementation, and maintenance of data pipelines using Python and PySpark (secondary alternative: Java)


* Experience in performance and tuning to ensure jobs are running at optimal levels and no performance bottleneck


* Proficiency in Unix scripting, data structures, data serialization formats such as JSON, AVRO, Protobuf, or similar, big-data storage formats such as Parquet, Iceberg, or similar, data processing methodologies such as batch, micro-batching, or stream, one or more data modelling techniques such as Dimensional, Data Vault, Kimball, Inmon, etc., Agile meth...