Lead Data Platform Engineer – Payments

Socket.dev; Austin (TX); Hybrid; USD 180,000 - 250,000; Full time

Benefits offered by this job

Health care coverage

On-site wellness centers

Retirement savings plan

Tuition reimbursement

Mental health support

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer - Data and Payments Data Platform to join the Data Analytics Payments team in Austin. You will design and scale data pipelines, implement data models, and drive AI-assisted engineering practices across the SDLC to improve quality and delivery velocity.

You will collaborate with analytics, product, and business stakeholders to translate requirements into production-grade solutions, ensuring security, governance, and reliability at scale.

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.
• 3+ years of professional experience focused on data engineering or data platform development.

Responsibilities

• Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing.
• Develops data platform components including data cataloging, data quality frameworks, and governance features.
• Implements data modeling strategies to support analytics and reporting.
• Leads adoption of enterprise AI-assisted engineering practices for code quality and delivery speed.

Skills

Python

Java

SQL

Spark

Flink

Airflow

Databricks

Kubernetes

AI-assisted development

Education

Formal software engineering training

Certification in software engineering concepts

Tools

Spark

Airflow

Flink

Databricks

AWS (S3, Glue, Redshift, Athena, EMR)

Tableau or BI tooling

Terraform

Job description

JPMorgan Chase & Co. is seeking a Lead Software Engineer - Data and Payments Data Platform to join the Data Analytics Payments team in Austin. You will design and scale data pipelines, implement data models, and drive AI-assisted engineering practices across the SDLC to improve quality and delivery velocity.

You will collaborate with analytics, product, and business stakeholders to translate requirements into production-grade solutions, ensuring security, governance, and reliability at scale.