Sr Lead Software Engineer (Data Platform)

Be an integral part of an Agile team thats 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