Lead Software Engineer - AWS, Java/Scala/Python, Spark

Job 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 Data Platform Engineering - Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of 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
• 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, equity, inclusion, and respect

Required qualifications, capabilities, and skills

• 5+ years of experience working in big data environment, using AWS, Java /Python / Spark, Scala
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient in one or more object-oriented programming language(s) with expertise in languages such as Scala, Java, Python etc.
• Experience in Apache Spark for large-scale data processing.
• Proficient in application, data, and infrastructure architecture disciplines.
• Proficient in cloud-native architecture, design and implementation across all systems.
• Proficient in Event Driven Architecture.
• Proficient in Application Containerization.
• Proficient in building applications on Public Cloud (AWS, GCP, Azure) development with AWS experience being strongly preferred.
• Proficient in building applications for real-time streaming using Apache Spark Streaming, Apache Kafka, Amazon Kinesis etc.
• Proficient in building on emerging cloud serverless managed services, to minimize/eliminate physical/virtual server footprint.

Preferred qualifications, capabilities, and skills

• Proficient in designing and developing data pipelines using Databricks Lakehouse to ingest, enrich, and validate data from multiple sources.
• Proficient in re-engineering and migrating on-premises data solutions to and for the public cloud.
• Proficient in implementing security solutions for data storage and processing in the public cloud.
• Proficient understanding of traditional big data systems, such as Hadoop, Impala, Sqoop, Oozie, Cassandra, Hive, HBase etc.