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Lead Software Engineer - Data Platform

ChaseAustin, TXJune 6th, 2026
Lead Software EngineerWe 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 at JPMorgan Chase, within the Commercial & Investment Banking – Data Analytics – Payments Technology 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 responsibilitiesExecutes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problemsDesigns, builds, and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing using Spark, Airflow, Kafka, and FlinkDevelops data platform components including data cataloging, data quality frameworks, and semantic/metrics layers with embedded governance, lineage, and compliance standardsImplements data modeling strategies (fact and dimensional, wide tables) to support analytics, reporting, and downstream consumptionPartners with analytics teams, product managers, and business stakeholders to translate data requirements into production-grade solutionsDevelops secure high-quality production code, and reviews and debugs code written by othersIdentifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systemsLeads 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 architectureLeads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologiesAdds to team culture of diversity, opportunity, inclusion, and respectRequired qualifications, capabilities, and skillsFormal training or certification on software engineering concepts and 5+ years of applied experienceHands-on practical experience delivering system design, application development, testing, and operational stabilityDemonstrated professional experience focused on software engineering or data platform developmentAdvanced in one or more programming languages(s); Python, Java and SQLHands-on experience with distributed data processing frameworks such as Apache Spark and FlinkSolid understanding of data modeling techniques (star schema, snowflake) and query optimizationExperience designing and operating data pipelines on Databricks using orchestration tools such as Apache AirflowProficiency with cloud data services (AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, or equivalent)Experience engineering production-grade data platforms on Kubernetes with open catalog integration (e.g., Apache Iceberg, Unity Catalog, OpenMetadata) for scalable data discovery, lineage, and governance.Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and SecurityDemonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)Preferred qualifications, capabilities, and skillsExperience with Agentic AI, LLMs, RAG architectures, vector databases, and embedding-based retrieval systemsHands-on familiarity with Internal Developer Portals such as Backstage — including service catalog management, software templating, and plugin developmentExperience with data mesh or data product architecturesProficiency with Infrastructure as Code (Terraform) and containerized deployments (Docker, Kubernetes)Experience with data observability, quality, and metadata management toolsExperience with semantic layers, metrics stores, or BI platforms (Tableau, dbt Metrics)