JPMorgan Chase & Co.
Software Engineer III- ETL/ELT Pipelines / Python / Pyspark/ AWS
JPMorgan Chase & Co., New York, New York, us, 10261
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III- ETL/ELT Pipelines / Python / Pyspark / AWS at JPMorganChase within the Asset and Wealth Management Technology Team, you serve as a seasoned member of an agile team to design and deliver trusted market‑leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutionslassPrelude across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Design and implement scalable data solutions that align with business objectives and technology strategies and technical troubleshooting with ability to think beyond routine or conventional approaches to build and support solutions or break down technical problems Design, develop, and optimize robust ETL/ELT pipelines using SQL, Python, and PySpark for large‑scale, complex data environments Develop and support secure معتبر production code, and review and debug code written by others Support data migration and modernization initiatives, transitioning legacy systems to cloud‑based data warehouses Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Collaborate with cross‑functional teams to understand data requirements and translate them into technical specifications Monitor and tune ETL processes for efficiency, resilience and scalability, including alerting for data quality issues Work closely with stakeholders to identify opportunities for data‑driven improvements and efficiencies Document data flows, logic, and transformation rules to maintain transparency and facilitate knowledge sharing across teams Stay current on emerging ETL and data engineering technologies with industry trends to drive innovation Required qualifications, capabilities, and skills
Formal training or certification in software engineering with 3+ years of applied experience Proficient in coding in one or more languages including Python Strong hands‑on coding proficiency in Python, PySpark, Apache Spark, SQL, and with AWS cloud services such as AWS EMR, S3, Athena, Redshift Hands‑on experience with AWS cloud and data lake platforms, Snowflake, Databricks etc Proven experience in ETL/ELT pipeline development and with large‑scale data processing with SQL Practical experience implementing data validation, cleansing, transformation, and reconciliation processes to ensure high‑quality, trustworthy datasets Experience with cloud‑based data warehouse migration and modernization Proficiency in distributors and continuous delivery methods and understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Excellent problem‑solving and troubleshooting skills, with ability to optimize performance and troubleshoot complex data pipelines Strong communication and documentation abilities Ability to collaborate effectively with business and technical stakeholders Preferred qualifications, capabilities, and skills
Knowledge of Apache Iceberg Knowledge of the financial services industry and IT systems
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Design and implement scalable data solutions that align with business objectives and technology strategies and technical troubleshooting with ability to think beyond routine or conventional approaches to build and support solutions or break down technical problems Design, develop, and optimize robust ETL/ELT pipelines using SQL, Python, and PySpark for large‑scale, complex data environments Develop and support secure معتبر production code, and review and debug code written by others Support data migration and modernization initiatives, transitioning legacy systems to cloud‑based data warehouses Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Collaborate with cross‑functional teams to understand data requirements and translate them into technical specifications Monitor and tune ETL processes for efficiency, resilience and scalability, including alerting for data quality issues Work closely with stakeholders to identify opportunities for data‑driven improvements and efficiencies Document data flows, logic, and transformation rules to maintain transparency and facilitate knowledge sharing across teams Stay current on emerging ETL and data engineering technologies with industry trends to drive innovation Required qualifications, capabilities, and skills
Formal training or certification in software engineering with 3+ years of applied experience Proficient in coding in one or more languages including Python Strong hands‑on coding proficiency in Python, PySpark, Apache Spark, SQL, and with AWS cloud services such as AWS EMR, S3, Athena, Redshift Hands‑on experience with AWS cloud and data lake platforms, Snowflake, Databricks etc Proven experience in ETL/ELT pipeline development and with large‑scale data processing with SQL Practical experience implementing data validation, cleansing, transformation, and reconciliation processes to ensure high‑quality, trustworthy datasets Experience with cloud‑based data warehouse migration and modernization Proficiency in distributors and continuous delivery methods and understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Excellent problem‑solving and troubleshooting skills, with ability to optimize performance and troubleshoot complex data pipelines Strong communication and documentation abilities Ability to collaborate effectively with business and technical stakeholders Preferred qualifications, capabilities, and skills
Knowledge of Apache Iceberg Knowledge of the financial services industry and IT systems
#J-18808-Ljbffr