JPMorganChase
Lead Software Engineer: Data Engineer/PySpark/AWS/Databricks
JPMorganChase, Columbus, Ohio, United States, 43224
Lead Software Engineer: Data Engineer/PySpark/AWS/Databricks
Lead Software Engineer focused on data engineering within JPMorgan Chase's Corporate Sector. The role involves designing, developing, and delivering secure, scalable software components for data-intensive applications and platforms, with emphasis on data ingestion, processing, and analytics in financial services contexts. Responsibilities
Execute creative software solutions, design, development, and technical troubleshooting to build effective solutions and resolve technical challenges. Develop secure, high-quality production code; review and debug code to ensure optimal performance and security. Identify opportunities to automate remediation of recurring issues to improve operational stability of software applications and systems. Lead evaluation sessions with internal teams to assess architectural designs and their applicability within existing systems and information architecture. Lead communities of practice across Software Engineering to promote awareness and adoption of new technologies. Collaborate with business stakeholders to understand requirements and design appropriate solutions, producing architecture and design artifacts for complex applications. Implement robust monitoring and alerting to proactively identify and address data ingestion issues, optimizing performance and throughput. Implement data quality checks and validation processes to ensure data accuracy and reliability. Design and implement scalable data frameworks to manage end-to-end data pipelines for Financial Risk data analytics. Share and develop best practices with Platform and Architecture teams to enhance data pipeline frameworks and modernize the finance data analytics platform. Gather, analyze, and synthesize large, diverse data sets to continuously improve capabilities and user experiences using data-driven insights. Qualifications
Required
Formal training or certification in software engineering concepts and 5+ years of applied experience Comprehensive understanding of all aspects of the Software Development Life Cycle Advanced proficiency in data processing frameworks and tools (Parquet, Iceberg, PySpark, Databricks, Glue, Lambda, EMR, ECS, Aurora) Advanced knowledge of agile methodologies, including CI/CD, application resiliency, and security practices Proficiency in programming languages and experience with Apache Spark for data processing and application development Experience with scheduling tools like Autosys or Airflow Hands-on experience in system design, application development, testing, and ensuring operational stability Demonstrated expertise in cloud computing, AI/ML disciplines Proficiency in automation and continuous delivery methods Understanding of the financial services industry and its IT systems Preferred
Expertise in relational databases such as Oracle or SQL Server Oracle SQL querying skills (DML, DDL, PL/SQL) AWS certification Familiarity with Databricks for advanced data analytics About Us
JPMorgan Chase is an Equal Opportunity Employer. We value diversity and inclusion and do not discriminate on the basis of protected attributes. We provide reasonable accommodations for applicants and employees as needed. More details available during the hiring process. Locations and compensation details vary by role and location; eligible employees may receive base salary, incentives, and a comprehensive benefits package.
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Lead Software Engineer focused on data engineering within JPMorgan Chase's Corporate Sector. The role involves designing, developing, and delivering secure, scalable software components for data-intensive applications and platforms, with emphasis on data ingestion, processing, and analytics in financial services contexts. Responsibilities
Execute creative software solutions, design, development, and technical troubleshooting to build effective solutions and resolve technical challenges. Develop secure, high-quality production code; review and debug code to ensure optimal performance and security. Identify opportunities to automate remediation of recurring issues to improve operational stability of software applications and systems. Lead evaluation sessions with internal teams to assess architectural designs and their applicability within existing systems and information architecture. Lead communities of practice across Software Engineering to promote awareness and adoption of new technologies. Collaborate with business stakeholders to understand requirements and design appropriate solutions, producing architecture and design artifacts for complex applications. Implement robust monitoring and alerting to proactively identify and address data ingestion issues, optimizing performance and throughput. Implement data quality checks and validation processes to ensure data accuracy and reliability. Design and implement scalable data frameworks to manage end-to-end data pipelines for Financial Risk data analytics. Share and develop best practices with Platform and Architecture teams to enhance data pipeline frameworks and modernize the finance data analytics platform. Gather, analyze, and synthesize large, diverse data sets to continuously improve capabilities and user experiences using data-driven insights. Qualifications
Required
Formal training or certification in software engineering concepts and 5+ years of applied experience Comprehensive understanding of all aspects of the Software Development Life Cycle Advanced proficiency in data processing frameworks and tools (Parquet, Iceberg, PySpark, Databricks, Glue, Lambda, EMR, ECS, Aurora) Advanced knowledge of agile methodologies, including CI/CD, application resiliency, and security practices Proficiency in programming languages and experience with Apache Spark for data processing and application development Experience with scheduling tools like Autosys or Airflow Hands-on experience in system design, application development, testing, and ensuring operational stability Demonstrated expertise in cloud computing, AI/ML disciplines Proficiency in automation and continuous delivery methods Understanding of the financial services industry and its IT systems Preferred
Expertise in relational databases such as Oracle or SQL Server Oracle SQL querying skills (DML, DDL, PL/SQL) AWS certification Familiarity with Databricks for advanced data analytics About Us
JPMorgan Chase is an Equal Opportunity Employer. We value diversity and inclusion and do not discriminate on the basis of protected attributes. We provide reasonable accommodations for applicants and employees as needed. More details available during the hiring process. Locations and compensation details vary by role and location; eligible employees may receive base salary, incentives, and a comprehensive benefits package.
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