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 recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, and utilization 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 archiving strategy 
• Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms
• Creates functional and technical documentation supporting best practices​​
• 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

• 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