Lead Software Engineer - AWS, PySpark, Databricks

Description

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

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

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.

Develops secure high-quality production code, and reviews and debugs code written by others

Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

Leads 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

Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

Adds to 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 experience

7+ years of experience in Data Engineering, specifically design, application development, testing and operational stability

Advanced proficiency in data processing frameworks and tools, including knowledge of Parquet, Iceberg, PySpark, Glue, Lambda, Databricks and AWS.

Proficiency in automation and continuous delivery methods.

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

Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Demonstrated proficiency in software 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 Certification

Databricks Certification