Senior Data Engineer, Azure & Databricks (Remote)

ReviewTrackers; Northern (KY); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Press Ganey is seeking a Staff Data Engineer to join the Unified Data Platform team. You will design, build, and maintain enterprise-scale data infrastructure leveraging Azure and Databricks, enabling data-driven decision making across analytics, data science, and business teams.

The role focuses on robust data pipelines, data quality, governance, and secure, compliant data practices. You will mentor engineers, contribute to CI/CD for data workflows, and stay current with Delta Lake, Spark, and

Qualifications

• 7+ years of data engineering experience in cloud environments.
• Proven experience with Azure data services and Databricks.
• Strong SQL and Python programming skills.
• Experience with data modeling, governance, and metadata management.

Responsibilities

• Design, build, and maintain enterprise-scale data pipelines in Azure and Databricks.
• Lead data modeling, quality, and governance initiatives across the Unified Data Platform.
• Collaborate with analytics, data science, and business teams to enable data-driven decisions.
• Mentor junior engineers and contribute to engineering best practices.

Skills

Azure Data Platform

Databricks

Apache Spark

Delta Lake

SQL

Python

Git & CI/CD

Power BI

Data Modeling

Data Governance

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field

Tools

Git

Azure DevOps

Delta Lake tooling

Job description

Press Ganey is seeking a Staff Data Engineer to join the Unified Data Platform team. You will design, build, and maintain enterprise-scale data infrastructure leveraging Azure and Databricks, enabling data-driven decision making across analytics, data science, and business teams.

The role focuses on robust data pipelines, data quality, governance, and secure, compliant data practices. You will mentor engineers, contribute to CI/CD for data workflows, and stay current with Delta Lake, Spark, and