Senior Data Platform Engineer (AI-Driven)

JPMorganChase; Jersey City (NJ); On-site; USD 120,000 - 170,000; Full time

Job summary

JPMorganChase is seeking a seasoned software/data platform engineer to design and deliver scalable data pipelines and AI-enhanced solutions in a fast-paced financial services environment.

You will collaborate with analytics, product, and security teams to implement robust data models, governance, and cloud-based platforms using Spark, Airflow, Databricks, and AWS. The role emphasizes reliability, security, and production-grade code.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability and 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 building highly scalable, robust and fault tolerant API (REST, GraphQL).
• Experience designing and operating data pipelines on Databricks using orchestration tools such as Apache Airflow.
• Experience with AWS cloud platforms, including deploying and operating services in a cloud environment.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• 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, and and manages enterprise applications at scale to ensure robust and fault tolerant data processing and ingestion.
• 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
• Sets and upholds engineering standards for the team's Spring Boot services (API design, error handling, security, logging, performance tuning, versioning)
• Ensures production readiness through observability (metrics, logs, tracing), alerting, incident response runbooks, and proactive problem management and develops secure high-quality production code, and reviews and debugs code written by others
• Applies knowledge of SDLC toolchains, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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

Skills

Python

Java

SQL

Apache Spark

Apache Flink

Apache Airflow

REST API design

GraphQL

AWS Cloud

CI/CD

Security

Agile methodologies

AI-assisted development tools

Observability

Tools

Docker

Kubernetes

Terraform

Databricks

Clickhouse

Tableau

Sigma

dbt

Redshift

Job description

JPMorganChase is seeking a seasoned software/data platform engineer to design and deliver scalable data pipelines and AI-enhanced solutions in a fast-paced financial services environment.

You will collaborate with analytics, product, and security teams to implement robust data models, governance, and cloud-based platforms using Spark, Airflow, Databricks, and AWS. The role emphasizes reliability, security, and production-grade code.