J.P. Morgan
Embrace this pivotal role as an essential member of a high performing team dedicated to reaching new heights in data engineering. Your contributions will be instrumental in shaping the future of one of the world’s largest and most influential companies.
As a Senior Lead Data Engineer at JPMorgan Chase within the Consumer Community Banking Data Center Management team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way. You will leverage your deep technical expertise and problem solving capabilities to drive significant business impact and tackle a diverse array of challenges that span multiple data pipelines, data architectures, and other data consumers. You will work effectively across multiple teams to evaluate requirements and develop a data proposal that unifies all teams and aligns to enterprise standards. This role requires detailed understanding of modern data engineering solutions for large and complex data sets as well as the ability to develop a strategic plan, present it to senior management, and drive the implementation.
Job responsibilities
Develops and implements a comprehensive data strategy aligned with departmental and organizational goals
Collaborates with stakeholders to understand data requirements and translate them into technical solutions
Establishes data governance and quality standards to ensure data integrity and compliance
Evaluates and selects appropriate data technologies (databases, ETL tools, cloud platforms) to meet current and future needs
Optimizes data architecture and infrastructure for performance, reliability, and cost-effectiveness
Provides recommendationsandinsight on data management, governance procedures,andintricacies applicable to the acquisition, maintenance, validation, andutilization of data
Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
Defines database back-up,recovery, and archivingstrategy
Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms
Creates functional andtechnicaldocumentationsupporting bestpractices
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on
Data Engineering
concepts and 5+ years applied experience
Working experience with both relational and NoSQL databases
Advanced understanding of database back-up, recovery, and archiving strategies
Advanced knowledge of linear algebra, statistics, and geometrical algorithms
Experience presenting and delivering visual data
Hands on experience with ETL tools and data integration frameworks
Ability to communicate complex technical concepts to non-technical stakeholders.
Programming skills for data processing and automation
Knowledge of data governance, data quality, and security best practices
Experience with complex data models and data lakes
Strong Project Management skills, deals well with ambiguity; can shape and define the future, take an idea and turn it into execution
Preferred qualifications, capabilities, and skills
Experience with business intelligence tools (e.g., Tableau, Qlik) and enabling self-service analytics
Experience with cloud data platforms (e.g., AWS) and cloud-native data engineering tools
7+ years of related Data Engineering experience including designing and building data pipelines and architectures
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As a Senior Lead Data Engineer at JPMorgan Chase within the Consumer Community Banking Data Center Management team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way. You will leverage your deep technical expertise and problem solving capabilities to drive significant business impact and tackle a diverse array of challenges that span multiple data pipelines, data architectures, and other data consumers. You will work effectively across multiple teams to evaluate requirements and develop a data proposal that unifies all teams and aligns to enterprise standards. This role requires detailed understanding of modern data engineering solutions for large and complex data sets as well as the ability to develop a strategic plan, present it to senior management, and drive the implementation.
Job responsibilities
Develops and implements a comprehensive data strategy aligned with departmental and organizational goals
Collaborates with stakeholders to understand data requirements and translate them into technical solutions
Establishes data governance and quality standards to ensure data integrity and compliance
Evaluates and selects appropriate data technologies (databases, ETL tools, cloud platforms) to meet current and future needs
Optimizes data architecture and infrastructure for performance, reliability, and cost-effectiveness
Provides recommendationsandinsight on data management, governance procedures,andintricacies applicable to the acquisition, maintenance, validation, andutilization of data
Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
Defines database back-up,recovery, and archivingstrategy
Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms
Creates functional andtechnicaldocumentationsupporting bestpractices
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on
Data Engineering
concepts and 5+ years applied experience
Working experience with both relational and NoSQL databases
Advanced understanding of database back-up, recovery, and archiving strategies
Advanced knowledge of linear algebra, statistics, and geometrical algorithms
Experience presenting and delivering visual data
Hands on experience with ETL tools and data integration frameworks
Ability to communicate complex technical concepts to non-technical stakeholders.
Programming skills for data processing and automation
Knowledge of data governance, data quality, and security best practices
Experience with complex data models and data lakes
Strong Project Management skills, deals well with ambiguity; can shape and define the future, take an idea and turn it into execution
Preferred qualifications, capabilities, and skills
Experience with business intelligence tools (e.g., Tableau, Qlik) and enabling self-service analytics
Experience with cloud data platforms (e.g., AWS) and cloud-native data engineering tools
7+ years of related Data Engineering experience including designing and building data pipelines and architectures
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