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)
Job at a Glance
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.
Responsibilities
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Analyze, design, and develop enterprise data solutions using Azure, Databricks, Spark, Python, and SQL
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Develop, optimize, and maintain Spark/PySpark pipelines, including managing data skew, partitioning, caching, and shuffle optimization
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Build and support Delta Lake tables and data models for analytical and operational use cases
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Apply reusable design patterns, data standards, and architecture guidelines, including collaboration with internal clients when needed
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Use Terraform to provision and manage cloud and Databricks resources following Infrastructure as Code (IaC) practices
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Implement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deployment
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Manage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts
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Troubleshoot failures and improve reliability across Databricks jobs, clusters, and pipelines
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Apply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments
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Work with engineering teams to enhance tools, systems, development processes, and data security
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Participate in the development and communication of data strategy, standards, and roadmaps
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Draft architectural diagrams, interface specifications, and other design documents
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Promote reuse of data assets and support enterprise data catalog practices
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Deliver timely support and communication to stakeholders and end users
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Mentor team members on data engineering principles, best practices, and emerging technologies
Qualifications
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5+ years of experience as a Data Engineer
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Hands-on experience with Azure Databricks, Spark, and Python
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Experience with Delta Live Tables (DLT) or Databricks SQL
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Strong SQL and database background
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Experience with Azure Functions, messaging services, or orchestration tools
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Familiarity with governance, lineage, or cataloging tools such as Purview or Unity Catalog
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Experience monitoring and optimizing Databricks clusters or workflows
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Experience working with Azure cloud data services and understanding their integration with Databricks and enterprise platforms
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Experience with Terraform for cloud provisioning
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Experience with GitHub and GitHub Actions for version control and CI/CD automation
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Strong understanding of distributed computing concepts including partitions, joins, shuffles, and cluster behavior
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Familiarity with SDLC and modern engineering practices
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Ability to balance multiple priorities, work independently, and maintain organization
About the Client
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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