Data Engineer II

Job Description

Title: Data Engineer
Location: Blue Ash, OH
Duration: 6 Months (Contract or Contract-to-Hire)
Work Type: Onsite (local candidates strongly preferred)

The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands‑on skills in Databricks, Spark, Python, and cloud‑based Data Ops practices. The role includes analyzing, designing, and developing data products, pipelines, and information architecture deliverables with a focus on treating data as an enterprise asset. This position also supports cloud infrastructure automation and CI/CD using Terraform, Git Hub, and Git Hub Actions to deliver scalable, reliable, and secure data solutions.

• Analyze, design, and develop enterprise data solutions using Azure, Databricks, Spark, Python, and SQL
• Develop, optimize, and maintain Spark/PySpark pipelines, including managing data skew, partitioning, caching, and shuffle optimization
• Build and support Delta Lake tables and data models for analytical and operational use cases
• Apply reusable design patterns, data standards, and architecture guidelines, including collaboration with internal clients when needed
• 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 for source control, testing, and pipeline deployment
• Manage Git‑based workflows for Databricks notebooks, jobs, and data engineering artifacts
• Troubleshoot failures and improve reliability across Databricks jobs, clusters, and pipelines
• Apply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments
• Work with engineering teams to enhance tools, systems, development processes, and data security
• Participate in the development and communication of data strategy, standards, and roadmaps
• Draft architectural diagrams, interface specifications, and other design documents
• Promote reuse of data assets and support enterprise data catalog practices
• Deliver timely support and communication to stakeholders and end users
• Mentor team members on data engineering principles, best practices, and emerging technologies

• 5+ years of experience as a Data Engineer
• Hands‑on experience with Azure Databricks, Spark, and Python
• Experience with Delta Live Tables (DLT) or Databricks SQL
• Strong SQL and database background
• Experience with Azure Functions, messaging services, or orchestration tools
• Familiarity with governance, lineage, or cataloging tools such as Purview or Unity Catalog
• Experience monitoring and optimizing Databricks clusters or workflows
• Experience working with Azure cloud data services and understanding their integration with Databricks and enterprise platforms
• Experience with Terraform for cloud provisioning
• Experience with Git Hub and Git Hub Actions for version control and CI/CD automation
• Strong understanding of distributed computing concepts including partitions, joins, shuffles, and cluster behavior
• Familiarity with SDLC and modern engineering practices
• Ability to balance multiple priorities, work independently, and maintain organization

The client is a large, forward‑leaning technology organization focused on delivering modern, scalable data solutions across the enterprise. The team emphasizes cloud‑native engineering practices, strong data governance, and high‑quality data products that support analytics, operational insights, and digital transformation initiatives. Engineers collaborate in a fast‑paced, agile environment with a focus on innovation, reliability, and continuous improvement.