Senior Lead Software Engineer - Java / Python - Risk Technology Data Strategy
Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.
You'll work with Java, Python, Kafka, Redis, Airflow, Spark/PySpark, Snowflake, Databricks, and observability tools like Dynatrace and Splunk to design and build large-scale data engineering solutions for JPMorgan's Corporate Risk Technology Data Platform & Strategy team. This senior lead role involves architecting secure, scalable data platforms, leading technical strategy across teams, and driving innovation in enterprise data systems while fostering team culture and assessing external vendors.
Free Tailor for ATS: 10/10 runs left
Join us and shape the future of risk technology with your expertise in data engineering and software development. You will have the opportunity to push boundaries, innovate, and make a meaningful impact on our business. We value diversity, inclusion, and respect, fostering a collaborative environment where your ideas matter. Experience career growth and mobility while working with market-leading technology products. Be part of a team that thrives on creativity and continuous improvement.
As a Senior Lead Software Engineer at JPMorgan Chase within the Data Platform & Strategy team within Corporate Risk Technology, you will design, build, and enhance advanced data engineering solutions. You will play a pivotal role in delivering secure, stable, and scalable technology products that support our business objectives. You will collaborate with agile teams, contribute to technical strategy, and drive innovation across multiple technical areas. Your work will help shape the team culture and the impact of our technology solutions.
Job Responsibilities:
Execute creative software solutions, design, development, and technical troubleshooting to solve complex problems
Develop secure, high-quality production code for data-intensive applications and review code written by others
Identify opportunities to automate remediation of recurring issues and improve operational stability
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials
Drive communities of practice across Software Engineering to promote new and leading-edge technologies
Foster a team culture of opportunity, inclusion, and respect
Required Qualifications, Capabilities, and Skills:
Proficiency in Engineering & Architecture, AI/ML, with hands-on experience designing, implementing, testing, and ensuring operational stability of large-scale enterprise data platforms
Advanced skills in one or more programming languages such as Java, Python, C/C++, or C#
Practical experience delivering system design, application development, testing, and operational stability
Working knowledge of relational and NoSQL databases and data lake architectures
Experience developing, debugging, and maintaining code with modern programming languages and database querying languages
Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, Observability tools (Dynatrace, Splunk, Grafana), and Orchestration tools (Airflow, Temporal)
Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies, CI/CD, application resiliency, and security
Practical cloud-native experience
Preferred Qualifications, Capabilities, and Skills:
Experience with modern data technologies such as Databricks or Snowflake
Hands-on experience with Spark/PySpark and other big data processing technologies
Demonstrated proficiency in software applications and technical processes within disciplines such as data engineering, cloud, artificial intelligence, machine learning, or mobile
Knowledge of the financial services industry and their IT systems