Lead Data Platform Engineer: Scalable Pipelines

JPMorgan Chase & Co.; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. invites applications for a Lead Software Engineer in the Commercial & Investment Banking – Data Analytics – Payments Technology team.

You will be a core technical contributor, building trustworthy, scalable tech products, and shaping data pipelines end-to-end in a secure, production-grade environment. The role requires expertise across Python/Java/SQL, Spark, Flink, Airflow, and Databricks, with cloud services and Kubernetes experience.

Qualifications

• 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.
• Demonstrated professional experience focused on software 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).
• 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 Security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

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

Job description

JPMorgan Chase & Co. invites applications for a Lead Software Engineer in the Commercial & Investment Banking – Data Analytics – Payments Technology team.

You will be a core technical contributor, building trustworthy, scalable tech products, and shaping data pipelines end-to-end in a secure, production-grade environment. The role requires expertise across Python/Java/SQL, Spark, Flink, Airflow, and Databricks, with cloud services and Kubernetes experience.