Sr Lead Software Engineer (Data Platform)

JPMorgan Chase & Co.•Houston, TX

About The Position

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

Requirements

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

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