Lead Software Engineer Python (Data engineering)

Job Description As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Banks Equities Technology Prime Services team, you play a crucial role in an agile team dedicated to enhancing, building, and delivering top-notch technology products in a secure, stable, and scalable manner to support the firm's business objectives. **Key Responsibilities:** - Design and Implement data pipelines and data stores for quant models - Collaborate with Trading Desk, Production Support, Quantitative Researchers, and Global Technology teams on Data Products and Analytics - Develop software solutions with a focus on technical troubleshooting and innovative problem-solving - Create secure and high-quality production code and maintain synchronous algorithms - Produce architecture and design artifacts for complex applications, ensuring design constraints are met - Analyze, synthesize, and visualize large datasets for continuous improvement of software applications - Identify hidden problems and patterns in data to drive improvements in coding hygiene and system architecture - Lead communities of practice across Software Engineering to promote the use of new technologies - Contribute to a team culture of diversity, opportunity, inclusion, and respect **Qualifications Required:** - Formal training or certification in software engineering concepts with at least 5 years of applied experience - Advanced proficiency in Python for data engineering, particularly in capital markets equities - Ownership of data quality, observability, lineage, and governance in production environments - Strong knowledge of SQL, schema design for analytical and time series workloads, and performance tuning on columnar data - Expertise in data management on AWS (S3, Glue, Athena, MWAA) - Hands-on experience in system design, application development, testing, and operational data flows - Practical experience in cloud-native environments **Preferred Qualifications:** - Prior knowledge of Capital Markets - Familiarity with data streaming frameworks like Kafka, AMPS - Experience with KDB/q - Proficiency in manipulating datasets using Pandas, Numpy, Scikit **Additional Details:** - Required Experience: IC Please let me know if you need any further information. As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Banks Equities Technology Prime Services team, you play a crucial role in an agile team dedicated to enhancing, building, and delivering top-notch technology products in a secure, stable, and scalable manner to support the firm's business objectives. **Key Responsibilities:** - Design and Implement data pipelines and data stores for quant models - Collaborate with Trading Desk, Production Support, Quantitative Researchers, and Global Technology teams on Data Products and Analytics - Develop software solutions with a focus on technical troubleshooting and innovative problem-solving - Create secure and high-quality production code and maintain synchronous algorithms - Produce architecture and design artifacts for complex applications, ensuring design constraints are met - Analyze, synthesize, and visualize large datasets for continuous improvement of software applications - Identify hidden problems and patterns in data to drive improvements in coding hygiene and system architecture - Lead communities of practice across Software Engineering to promote the use of new technologies - Contribute to a team culture of diversity, opportunity, inclusion, and respect **Qualifications Required:** - Formal training or certification in software engineering concepts with at least 5 years of applied experience - Advanced proficiency in Python for data engineering, particularly in capital markets equities - Ownership of data quality, observability, lineage, and governance in production environments - Strong knowledge of SQL, schema design for analytical and time series workloads, and performance tuning on columnar data - Expertise in data management on AWS (S3, Glue, Athena, MWAA) - Hands-on experience in system design, application development, testing, and operational data flows - Practical experience in cloud-native environments **Preferred Qualifications:** - Prior knowledge of Capital Markets - Familiarity with data streaming frameworks like Kafka, AMPS - Experience with KDB/q - Proficiency in manipulating datasets using Pandas, Numpy, Scikit **Additional Details:** - Required Experience: IC Please let me know if you need any further information.