Lead Software Engineer - Python, AWS

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 experience
• Practical 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 services

• Familiar 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).