Senior Python Backend Engineer — Databricks

JPMorganChase; Plano (TX); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health coverage

On-site health centers

Retirement plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorganChase in Plano, TX is seeking a Software Engineer III to design, build, and maintain scalable backend data engineering solutions that power critical financial reporting and analytics across the firm.

You will work with cross-functional teams to deliver reliable data pipelines on Databricks, with a focus on Python and PySpark, while applying secure coding standards and contributing to architecture decisions in an enterprise setting.

Qualifications

• 3+ years of software engineering experience.
• Experience with Python and PySpark in production environments.
• Experience with Databricks module development, deployment and support.
• Experience with AI-assisted development tools and evaluating outputs.
• Understanding of secure coding and data governance practices.
• Familiarity with CI/CD and security practices.

Responsibilities

• Develop, test, and troubleshoot backend data engineering solutions.
• Build and maintain PySpark data pipelines on Databricks.
• Collaborate with teams to translate finance requirements into scalable solutions.
• Produce architecture/design artifacts and ensure constraints are met.
• Contribute to code reviews and improve engineering standards.

Skills

Python backend development

PySpark

Databricks

AI-assisted development tools

CI/CD

Agile methodologies

Data engineering practices

Education

Formal software engineering training or certification

Tools

Databricks

Apache Spark

Kafka

AWS

Airflow

Terraform

Job description

JPMorganChase in Plano, TX is seeking a Software Engineer III to design, build, and maintain scalable backend data engineering solutions that power critical financial reporting and analytics across the firm.

You will work with cross-functional teams to deliver reliable data pipelines on Databricks, with a focus on Python and PySpark, while applying secure coding standards and contributing to architecture decisions in an enterprise setting.