Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.As a Lead Data Engineer at JPMorgan Chase within the Legal Technology Team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.Job responsibilities Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database back-up, recovery, and archiving strategy Evaluates and reports on access control processes to determine effectiveness of data asset security" with minimal supervision Builds solutions using AWS Cloud Services for compute, storage, databases, and security 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 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 Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5 years applied experience Experience and proficiency across the data and software development lifecycle Hands on Experience with AWS Cloud Services and strong understanding of AWS networking, security, IAM roles, monitoring and application debugging Advanced experience in Python and distributed computing frameworks such as PySpark Expertise working on AWS Cloud Based applications development using AWS Cloud Formation, Redshift, IAM and S3 Hands-on Experience using an IAC tools such as Terraform Hands-on experience building AWS data pipelines using Lambda, SQS, SNS, AWS Athena, Glue, EMR Proficiency in automation and continuous delivery methods Proficiency with ETL tools ( Informatica) and data analytics tools (Splunk, Cloudwatch, Datadog metrics) Advanced understanding of Agile methodologies such as CI/CD, Application Resiliency, and Security Preferred qualifications, capabilities, and skills Experience with Data Migrations from a on-premise database to cloud. Experience working with ML-Ops projects Experience building test automation frameworks for Data lake AWS Certifications