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Databricks Platform Engineer

SoTalent · Columbus, OH

Spotted 3d agoFull-time

Job details

Work mode
Hybrid
Employment
Full-time
Level
Mid level
Experience
4+ years
Education
Bachelor's degree
Posted
Oct 7, 2026
Last confirmed open
Oct 8, 2026
Job description

About this role

Databricks Platform Engineer

📍 Location: Columbus, Ohio, United States (On-site)

🏢 Industry: Hospitals and Health Care

💼 Work Setting: Hybrid

Are you passionate about building and optimizing modern cloud data platforms that power enterprise analytics and data-driven decision-making? We are seeking a Databricks Platform Engineer to support the scalability, reliability, and security of a cloud-based data ecosystem.

In this role, you will leverage your expertise in platform administration, cloud infrastructure, automation, and data engineering to enable high-quality data solutions while collaborating with cross-functional teams to enhance operational excellence.

Key Responsibilities

Data Platform Operations

  • Administer, maintain, and optimize Databricks environments supporting analytics and data engineering workloads.
  • Manage platform configurations, cluster performance, capacity planning, and operational stability.
  • Monitor platform health and troubleshoot performance, reliability, and operational issues.
  • Support the lifecycle management of platform resources across development, testing, and production environments.

Cloud Infrastructure & Automation

  • Develop and maintain Infrastructure as Code (IaC) solutions using Terraform or similar tools.
  • Support and optimize cloud-based data infrastructure within enterprise cloud environments.
  • Implement automation solutions to improve platform reliability, consistency, and operational efficiency.
  • Collaborate with infrastructure and security teams to align with organizational standards and best practices.

Data Engineering Enablement

  • Build and support data ingestion frameworks and pipelines that facilitate reliable data movement across systems.
  • Partner with Data Engineers to improve platform capabilities and optimize large-scale data processing workloads.
  • Support structured and unstructured data workloads in cloud-native environments.
  • Identify and resolve performance bottlenecks impacting data processing and accessibility.

Governance & Security

  • Support enterprise data governance initiatives and platform governance capabilities.
  • Implement and maintain data access controls, permissions, and security standards.
  • Ensure compliance with data management, security, and governance requirements.
  • Contribute to metadata management, data lineage, and data quality initiatives.

Continuous Improvement

  • Evaluate emerging technologies and platform enhancements to drive innovation.
  • Recommend and implement improvements that increase scalability, reliability, and developer productivity.
  • Document platform standards, operational procedures, and support processes.
  • Participate in incident response, root cause analysis, and operational reviews.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
  • 4+ years of experience in Data Engineering, Data Platform Engineering, Cloud Engineering, or a related discipline.
  • Hands-on experience administering Databricks environments.
  • Strong experience with Terraform and Infrastructure as Code practices.
  • Experience supporting cloud infrastructure and services.
  • Experience developing and maintaining data ingestion and integration solutions.
  • Strong SQL, troubleshooting, and problem-solving skills.
  • Experience supporting production environments and operational workloads.
  • Solid understanding of data modeling, data governance, and modern data architecture principles.

Preferred Qualifications

  • Experience with data governance and catalog solutions within modern data platforms.
  • Experience with cloud data technologies such as data lakes, data warehouses, or analytics platforms.
  • Proficiency in Python and automation for data engineering workloads.
  • Experience working in large-scale cloud analytics environments.
  • Knowledge of CI/CD pipelines and deployment automation practices.
  • Experience working within highly regulated industries.

Education

  • Bachelor's degree in Computer Science, Information Technology, Engineering, Information Systems, or a related field.
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