Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the CIB Data & Analytics Platform and 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

 

Implements and delivers engineering solutions/tools and data products using cloud and on-premises data, distributed computing and emerging technologies. Develops secure and high-quality production code, and reviews and debugs code written by others. Contributes through the full software development lifecycle including architecture, proofs of concept, prototyping, development, rollout and support.  Prioritize solving customer requests and issue reports, participate in support coverage Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software  Development Life Cycle Adds to the team culture of diversity, equity, inclusion, and respect

 

Required qualifications, capabilities, and skills

Formal training or certification on Computer Science / Engineering concepts and 5+ years hands on professional experience in building complex software systems in both private and public cloud environments (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 skill in Java and Python.   Strong hands-on experience with PostgreSQL, AWS RedShift, Athena, Glue, Kafka and  NoSQL (Cassandra, MongoDB).  Experience with fundamental DevOps practices including CI/CD. Ability to tackle design and functionality problems independently. A self-starter and thrive in a fast-paced, agile setting.  Have clear and effective verbal and written communication skills and ability to communicate seamlessly across tech and data scientist teams Preferred qualifications, capabilities, and skills Excellent problem-solving and analytical skills Containers and cloud proficiency including Docker, Kubernetes, AWS Hands on experience in building ETL/Data Pipeline and data lake platforms (e.g. Databricks, Spark/Hadoop, and Snowflake) Knowledge of workflow orchestration tools (e.g. Apache Airflow), integration technologies (e.g. GraphQL, REST) Experience building, deploying Machine Learning models, and the ML Lifecycle