Job Description

Job Description

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 DataOps 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, GitHub, and GitHub 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 GitHub and GitHub 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 GitHub and GitHub 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.

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