We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology Workforce Data Analytics team, you play a crucial role in an agile team dedicated to enhancing, building, and delivering trusted, market-leading technology products that are secure, stable, and scalable. As a key technical contributor, you are tasked with implementing critical technology solutions across multiple technical domains, supporting various business functions to achieve the firm’s business objectives.

 

Job Responsibilities:

Execute creative data solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems.Develop secure high-quality production data pipelines, and review and debug data processes implemented by others.Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of data applications and systems.Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.Lead communities of practice across Data Engineering to drive awareness and use of new and leading-edge technologies.Contribute to a team culture of diversity, opportunity, inclusion, and respect.

Required Qualifications, Capabilities, and Skills:

Formal training or certification on software engineering concepts and 5+ years applied experience3+ years of experience in Data Engineering, specifically design, application development, testing and operational stability in Python, PySpark, Glue, Lambda, Databricks and AWS .Knowledge of Unity Catalog, data formats including Delta tables, Iceberg tables.Hands-on practical experience delivering system design, application development, testing, and operational stability.Advanced proficiency in data processing frameworks and tools, including knowledge in Parquet and Iceberg.Proficiency in automation and continuous delivery methods.Proficient in all aspects of the Software Development Life Cycle.Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.Demonstrated proficiency in data applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).In-depth knowledge of the financial services industry and their IT systems.Practical cloud-native experience.

Preferred Qualifications, Capabilities, and Skills:

AWS CertificationDatabricks Certification