Senior Data Engineer: Databricks, Spark & AWS

Fairygodboss; Columbus (OH); On-site; USD 110,000 - 160,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III to join the Employee and Experience Technology team in a fast-paced, agile environment. You will design and deliver trusted data products, modernize with a Databricks-on-AWS lakehouse, and build secure, scalable pipelines using PySpark on Databricks.

You will work across data engineering, analytics, and operations to ensure data quality, reliability, and performance, while leveraging AI-assisted tools to accelerate development and improve outcomes.

Qualifications

• 3+ years of applied experience in data engineering and software development.
• Advanced PySpark experience on Databricks with Delta Lake patterns.
• Strong Python programming for data processing; Java/Scala a plus.
• Proficient in AWS data services (S3, EMR, Glue, Lambda, Athena) and Parquet/Iceberg formats.
• Experience with CI/CD and agile practices; data security and operational stability.

Responsibilities

• Design, build, and maintain Databricks PySpark data pipelines for workforce analytics.
• Tune PySpark jobs and Databricks clusters for performance and cost.
• Implement scalable data frameworks with bronze/silver/gold lakehouse patterns.
• Apply Delta Lake/Delta Live Tables for data quality and validation.
• Set up monitoring and alerts using Databricks and AWS CloudWatch.
• Automate remediation using Databricks Workflows and AWS tools.
• Deliver curated data to BI partners using Sigma, Tableau, and Alteryx.
• Collaborate with stakeholders and produce architecture/design artifacts.

Skills

Apache Spark (PySpark)

AWS ecosystem

Python

CI/CD

SQL

Airflow

Autosys

Databricks

Delta Lake

Delta Live Tables

GitHub Copilot

Claude

Sigma/Tableau/Alteryx

Tools

Databricks

Delta Lake

Delta Live Tables

Airflow

Autosys

GitHub Copilot

Claude

Sigma

Tableau

Alteryx

Job description

JPMorganChase is seeking a Software Engineer III to join the Employee and Experience Technology team in a fast-paced, agile environment. You will design and deliver trusted data products, modernize with a Databricks-on-AWS lakehouse, and build secure, scalable pipelines using PySpark on Databricks.

You will work across data engineering, analytics, and operations to ensure data quality, reliability, and performance, while leveraging AI-assisted tools to accelerate development and improve outcomes.