JPMC
Lead Software Engineer-Cloud Data/Python/Java/Spark
- Compensation
- Not disclosed
- Location
- Wilmington, DE, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Full 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-Cloud Data/Python/Java/Spark at JPMorgan Chase within the Consumer and Community Banking's Home Lending and Servicing team, you will play a crucial role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products that are secure, stable and scalable.
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
- 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
- Architect, develop, and deploy scalable data pipelines and solutions on AWS using services such as S3, Redshift, Glue, EMR, Lambda, and Athena
- Create and optimize data models, build robust ETL processes, and ensure efficient ingestation, transformation, and storage
- Monitor, troubleshoot, and tune data pipelines and cloud resources for optimal performance, reliability, and cost efficiency
- Maintain comprehensive documentation of data architectures, processes and best practices; mentor junior engineers and share knowledge within the team
- Stay current with AWS advancements, evaluate new services and tools, and drive continuous improvement in cloud data engineering practices
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Hands-on professional experience in one or more programming language(s), including Java or Python, proficiency in Python, SQL, and at least one additional language (e.g. Java or Scala) for data engineering tasks
- Hands-on experience utilizing Apache Spark for large-scale data processing, including developing and optimizing data pipelines, performing real-time and batch analytics, and leveraging Spark’s libraries for machine learning and data transformation to drive actionable business insights.
- Experience with infrastructure automation tools such as AWS CloudFormation or Terraform