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 Senior 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