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 AI/ML & Data Platform team, 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

Design, develop, and maintain ETL processes (using Python, AWS) to support data integration and data warehousing solutions.Collaborate with data architects, data analysts, and business stakeholders to understand data requirements and translate them into technical specifications.Optimize and tune ETL processes (using Python, AWS) for performance and scalability.Ensure data quality and integrity through rigorous testing and validation procedures.Monitor and troubleshoot ETL processes to resolve issues and ensure timely data availability.Develop and maintain documentation for ETL processes, data flows, and data models.Mentor and provide guidance to junior ETL engineers and data team members..

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experiencePractical experience in ETL development using Python and AWS, with a focus on data engineering.Proficient in debugging, optimization, and understanding various data formats (CSV, Parquet, ORC) and sources (HDFS, S3, SFTP, Apache Iceberg).Expertise in the Software Development Life Cycle and advanced knowledge of agile methodologies, including CI/CD, application resiliency, and security.Familiarity with programming languages such as Java or Scala.Experience with cloud platforms like AWS, Azure, or GCP and their data servicesPreferred qualifications, capabilities, and skillsFamiliar with big data technologies (e.g., Hadoop).Preferred experience with Apache Spark and strong SQL skills for relational databases like Oracle, SQL Server, and MySQL.Data governance and data security best practices.Familiar with real-time data processing and streaming technologies (e.g., Kafka, Flink).