Lead Data Platform Engineer - AI & Lakehouse

JPMorganChase

Jersey City (NJ)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

JPMorganChase in Jersey City is seeking a Lead Software Engineer to join the Commercial & Investment Banking Data Analytics - Payments Technology team, delivering trusted, scalable data products in a secure environment. You will develop production-grade solutions, collaborate with analytics teams, and advance data platforms across multiple domains.

The role emphasizes building and maintaining data pipelines, implementing governance, and driving high-quality software with modern tools and cloud

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: 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 for scalable data discovery, lineage, and governance.
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
Experience developing Agentic AI, LLMs, RAG architectures, MCP, vector databases, and embedding-based retrieval systems.

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 automate remediation of recurring issues to improve 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.
Leads development of the Agentic Autonomous Lakehouse capability - automating governed self-service pipeline provisioning and lakehouse operations (health/cost/performance analysis).
Leads communities of practice across Software Engineering to drive awareness and use of new technologies.
Adds to team culture of diversity, opportunity, inclusion, and respect.