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 Commercial & Investment Bank - Digital Client Relationship team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way. You 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 data pipelines, data architectures and other data consumers

Job Responsibilities

• Designs and builds hybrid on-prem and public cloud data platform solutions
• Designs and builds end-to-end data pipelines for ingestion, transformation, and distribution, supporting both batch and streaming workloads
• Develops and owns data products that are reusable, well-documented, and optimized for analytics, BI, and AI/ML consumers
• Implements and manages modern data lake and Lakehouse architectures, including Apache Iceberg table formats
• Implements interoperability across data platforms and tools, including Databricks, Snowflake, Amazon Redshift, AWS Glue, and Lake Formation
• Establishes and maintains end-to-end data lineage to support observability, impact analysis, and regulatory requirements
• Implements data quality validation and monitoring using frameworks such as Great Expectations
• Provides recommendations and insight on data management and governance procedures and intricacies applicable to the acquisition, maintenance, validation, and utilization of data
• Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Defines database back-up, recovery, and archiving strategy
• Creates functional and technical documentation supporting best practices. Advises junior engineers and technologists
   

Required qualifications, capabilities, and skills

• Formal training or certification on computer science concepts or equivalent and 5+ years applied experience
• Hands-on experience building and operating batch and streaming data pipelines at scale
• Experience with Apache Iceberg and modern table formats in Lakehouse environment
• Strong proficiency with Databricks, Snowflake, Amazon Redshift, and AWS data services such as Glue and Lake Formation
• Experience implementing data lineage, data quality, and data observability frameworks
• Working experience with both relational and NoSQL databases
• Advanced understanding of database back-up, recovery, and archiving strategy

• Experience presenting and delivering visual data

   

Drive significant business impact and tackle a diverse array of challenges that span multiple technologies and applications