Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact.
As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on-premises and cloud based infrastructure to deliver third party data to multiple lines of business. You will be working within an Agile project environment collaborating closely with cross-functional teams to deliver high-quality solutions to our clients.
Job Responsibilities
- Applies deep technical expertise and problem-solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions
- Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.
- Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use-cases
- Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements
- Capable of finding a balance between best of breed and cost effective solutions
- Act as a positive team player who is capable of accepting different intellectual points of view
- Clear and concise communicator; ability to present to senior management
- Ability to analyze and articulate problems and provide input into solutions
- Provide 3rd level support to operational roles
- A respect for strong process and control management disciplines
- Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.
Required qualifications, capabilities, and skills
- Formal training or certification on infrastructure engineering concepts and advanced applied experience in Cloud technologies including Kubernetes, Terraform and AWS
- Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation)
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations
- Network architecture and protocols
- Programming languages (e.g. Java, Python, C++)
- Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.)
- Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&P)
- Database technologies and SQL scripting
- Monitoring tools (ITRS Geneos, Dynatrace, Datadog)