Location: Jersey City, NJ, United States

Bring your engineering skills to the next level where your expertise will drive the development of cutting-edge Data, Analytics, and AI/ML Platforms. 

As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment - Data & Analytics Platforms Engineering team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. In this role you will drive significant business impact through your capabilities and contributions and apply deep technical ability and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

 

Job responsibilities

• Implements and builds firm-wide Data and AI platforms on cloud/on-premise with distributed computing and emerging technologies.
• Develops secure and high-quality production code, and review and debug code written by others.
• Contributes through the full software development lifecycle, including architecture, proofs of concept, prototyping, development, rollout, and support.
• Prioritizes solving customer requests and issue reports and take part in support coverage.
• Actively contributes to the engineering community as an advocate of firm-wide frameworks, tools, and practices of the Software Development Life Cycle.
• Collaborates with cross-functional teams to align platform capabilities with business needs and strategic goals.

 

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on professional experience in building complex/large-scale Data and AI Platforms in both private and public cloud environments (e.g., AWS).
• Degree in Computer Science, Computer Engineering, Mathematics, or a related technical field.
• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge of application, data, cloud, and infrastructure architecture disciplines.
• Advanced hands-on skills in Java and/or Python programming.
• Extensive hands-on experience with Databricks/Unity Catalog, Snowflakes, AWS RedShift, AWS Athena, Glue, Lakeformation, Kafka, PostgreSQL, and NoSQL (Cassandra, MongoDB).
• Hands-on experience with DevOps (CI/CD) practices, including Terraform; Containers and cloud ability, including Docker, Kubernetes, etc.
• Ability to tackle design and functionality problems independently. A self-starter who thrives in a fast-paced, agile setting.
• Clear and effective verbal and written communication skills and the ability to communicate seamlessly across business, product, tech and data scientist teams.

Preferred qualifications, capabilities, and skills

 

• Hands-on experience in building ETL/Data Pipeline and data platforms (e.g., Databricks, Spark/Hadoop, and Snowflake).
• Knowledge of workflow orchestration tools (e.g., Apache Airflow), integration technologies (e.g., GraphQL, REST), open table formats (e.g. Apache Iceberg, Delta Lake), data security & access control (coarse-grained vs fine-grained)
• Experience building AI/ML/GenAI applications, deploying Machine Learning models, and MLOps/LLMOps Lifecycle

 

 

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team