Software Engineer III, Data Engineer

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $174k

$128k $220k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $137,325–$211,200.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Software Engineer III, Data Engineer

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As a Software Engineer III- Data Engineer(Python, Databricks and AWS) within the Corporate Sector, you will join an agile team to design and deliver trusted data collection, storage, access, and analytics solutions. You are responsible for building and maintaining robust data pipelines and architectures that support the entire data engineering lifecycle, including ETL processes, data models, and data warehouses. You will develop end-to-end pipelines using Databricks, Apache Spark, and AWS services like S3, Redshift, and Lambda. Your daily work involves workflow orchestration with Airflow, processing streaming data via Kafka, and writing efficient Python and SQL code. You will also support AI and machine learning initiatives by engineering data for model development while utilizing enterprise-authorized AI capabilities to accelerate design analysis and documentation within a secure environment.

Skills

Databricks Apache Spark AWS Python SQL Airflow Kafka S3 Redshift Lambda ETL Data Modeling Data Warehousing Docker Kubernetes Machine Learning Agile

What you'll do

Design, develop, and optimize end-to-end data pipelines using Databricks, Apache Spark, and AWS.
Implement and manage workflow orchestration using Airflow.
Integrate and process streaming data using Kafka.
Write efficient, maintainable code in Python and SQL for data processing and analysis.
Develop and maintain ETL processes, data models, and data warehouses.
Use enterprise-authorized AI to accelerate pipeline design, documentation, and test generation while validating all outputs.
Prepare and engineer data to support AI and machine learning model development and deployment.
Monitor, troubleshoot, and optimize data workflows for performance, reliability, and security.

What we're looking for

Formal training or certification on data engineering concepts and 3+ years of applied experience.
Proven experience in the full lifecycle of data engineering, from ingestion to production.
Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows with strong validation habits.
Ability to review and validate AI-assisted outputs while following data handling requirements.
Strong hands-on expertise with Databricks, Apache Spark, AWS (S3, Redshift, Lambda, etc.), Airflow, and Kafka.
Proficiency in Python programming and SQL for data manipulation and analysis.
Experience with data modeling, ETL development, and data warehousing.
Certifications in relevant technologies such as AWS, Databricks, or Spark (preferred).