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We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Sr. Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Post Trade Technology team , you will also be accountable for identifying and mitigating data risks throughout the data life cycle in compliance with Firmwide policies and standards. You will serve as a member of the product team, collaborating with the Product Owner, design, and technology leads to ensure that the product delivers data in a manner consistent with the quality and safety requirements of the business. You will also partner with their aligned Data & Analytics lead to drive increased business value through the identification of data required to support analytics outcomes.
Job responsibilities
Required qualifications, capabilities, and skills
JPMorgan Chase Bank, N.A., doing business as Chase Bank or often as Chase, is an American national bank headquartered in New York City, that constitutes the consumer and commercial banking subsidiary of the U.S. multinational banking and financial services holding company, JPMorgan Chase
Job ID: 152154995
Skills:
messaging platforms , Data Management, Graphql, REST, Swagger, Apache Kafka, Data Governance, Data Privacy, data analysis tools, API concepts, event-driven architectures, Regulatory Requirements, AI-assisted software development tools, OpenAPI
Skills:
Data Management, Graphql, REST, Swagger, Apache Kafka, Data Governance, Data Privacy, data analysis tools, API concepts, event-driven architectures, Regulatory Requirements, AI-assisted software development tools, OpenAPI
Skills:
designing scalable data storage solutions, Collibra Data Governance, data governance principles and frameworks, data modeling techniques, integration strategies
Skills:
Metadata Management, Adf, Pyspark, Azure Databricks, Data Lineage, Sql, Data Warehousing, Databricks SQL, Purview, Lakehouse architectures, Unity Catalog, Synapse, ADLS, Azure Data Services
Skills:
Rabbitmq, Data Security, Kafka, Infrastructure Management, ETL frameworks, Airflow, large-scale messaging systems, dbt, workflow or orchestration frameworks, metrics stores