Cloud Data Engineer - Databricks & GCP for Finance

Cardinal Health; Frankfort (KY); On-site; USD 95,000 - 122,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

PTO

HSA

401k

Early pay access

FSAs

Disability insurance

Work-Life resources

Parental leave

Healthy lifestyle programs

Job summary

Cardinal Health is seeking a Data Engineer within the Digital Solutions Finance team to design, develop, and maintain robust data pipelines and architectures for analytical and operational needs. The role focuses on Databricks and Google Cloud Platform to ingest, process, and transform large-scale datasets, requiring a strong foundation in data engineering and cloud data warehouses.

You will collaborate with data scientists, analysts, and business stakeholders to deliver reliable datasets,

Qualifications

• Bachelor’s degree or equivalent practical experience.
• Strong SQL and at least one programming language (Python/Scala/Java).
• Experience with Databricks and GCP ecosystem (BigQuery, Cloud Storage, IAM).

Responsibilities

• Design, build, and optimize scalable data pipelines using Databricks and GCP services.
• Collaborate with data scientists, analysts, and stakeholders to deliver high-quality datasets.
• Implement data quality checks, monitoring, and alerting for data reliability.
• Participate in code reviews and establish data engineering best practices.
• Perform performance tuning to optimize processing times and minimize cloud costs.
• Assist in migrating legacy workflows to modern cloud platforms.

Skills

SQL

Python/Scala/Java

Databricks

GCP

Data modeling

ETL/ELT

Cloud data warehouses

Education

Bachelor’s degree in CS/IT or related field

Tools

Databricks

GCP

BigQuery

Job description

Cardinal Health is seeking a Data Engineer within the Digital Solutions Finance team to design, develop, and maintain robust data pipelines and architectures for analytical and operational needs. The role focuses on Databricks and Google Cloud Platform to ingest, process, and transform large-scale datasets, requiring a strong foundation in data engineering and cloud data warehouses.

You will collaborate with data scientists, analysts, and business stakeholders to deliver reliable datasets,