Additional Information
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer - Data and Payments Data Platform at JPMorgan Chase within the Commercial and Investment Banking - Data Analytics Payment 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing using Spark, Airflow, Kafka, and Flink
Develops data platform components including data cataloging, data quality frameworks, and semantic/metrics layers with embedded governance, lineage, and compliance standards
Implements data modeling strategies (fact and dimensional, wide tables) to support analytics, reporting, and downstream consumption
Partners with analytics teams, product managers, and business stakeholders to translate data requirements into production-grade solutions
Develops secure high-quality production code, and reviews and debugs code written by others
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years of applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
3+ years of professional experience focused on data engineering or data platform development
Advanced in one or more programming languages(s); Python, Java and SQL
Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink
Solid understanding of data modeling techniques (star schema, snowflake) and query optimization
Experience designing and operating data pipelines on Databricks using orchestration tools such as Apache Airflow
Proficiency with cloud data services (AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, or equivalent)
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills
Exposure to LLMs, RAG architectures, vector databases, and embedding-based retrieval systems
Experience with data mesh or data product architectures
Proficiency with Infrastructure as Code (Terraform) and containerized deployments (Docker, Kubernetes)
Experience with data observability, quality, and metadata management tools
Experience with semantic layers, metrics stores, or BI platforms (Tableau, dbt Metrics)