Data Engineer Level 2

Location: Cincinnati, OH
Salary: $65.00 USD Hourly - $70.00 USD Hourly
Description:

About the Role
We are seeking an experienced Data Engineer with strong hands-on expertise in building and operating modern data solutions on Azure. You will design, develop, and optimize data pipelines and data platforms using Databricks, Spark, Python, and cloud-native Data Ops practices. The role also involves supporting infrastructure automation and CI/CD processes using Terraform, Git Hub, and Git Hub Actions, ensuring the delivery of scalable, secure, and reliable enterprise data solutions.
Minimum Qualifications

• 5+ years of experience as a Data Engineer
• Strong hands-on experience with Azure Databricks, Spark, and Python
• Experience with Delta Live Tables (DLT) or Databricks SQL
• Strong SQL skills and a solid background in relational and distributed databases
• Experience with Azure Functions, messaging systems, or orchestration tools
• Familiarity with data governance, lineage, and catalog solutions (e.g., Purview, Unity Catalog)
• Experience monitoring and optimizing Databricks clusters and workflows
• Understanding of Azure cloud data services and their integration with Databricks
• Proficiency with Terraform for infrastructure provisioning
• Experience with Git Hub and Git Hub Actions for version control and CI/CD pipeline automation
• Strong understanding of distributed computing concepts (joins, shuffles, partitions, cluster behavior)
• Familiarity with modern SDLC and engineering best practices
• Ability to work independently, manage multiple priorities, and stay organized

Preferred Qualifications

• Experience with enterprise-scale data platform engineering
• Strong communication, documentation, and cross-team collaboration skills
• Ability to guide teams on data engineering best practices and emerging technologies

Key Responsibilities

• Design and develop large-scale data solutions using Azure, Databricks, Spark, Python, and SQL
• Build, optimize, and maintain Spark/PySpark pipelines, addressing performance tuning, data skew, partitioning, caching, and shuffle optimization
• Create and manage Delta Lake tables and data models for analytical and operational workloads
• Apply reusable design patterns, data standards, and architecture guidelines across the organization
• Use Terraform to provision and manage cloud and Databricks resources following Infrastructure-as-Code (IaC) practices
• Implement and maintain CI/CD workflows using Git Hub and Git Hub Actions
• Manage Git-based workflows for notebooks, jobs, and data engineering artifacts
• Troubleshoot pipeline issues and improve stability across Databricks jobs, workloads, and clusters
• Deploy fixes, optimizations, and enhancements in Azure environments
• Collaborate with engineering and architecture teams to enhance tooling, processes, and data security
• Contribute to the development of data strategy, standards, and roadmaps
• Prepare architectural diagrams, interface specifications, and technical documentation
• Promote the reuse of data assets and support enterprise metadata and cataloging practices
• Provide effective communication and support to stakeholders and end users
• Mentor teammates on data engineering principles, frameworks, and best practices

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Contact:

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