Title: Data Engineer
Location: Cincinnati OH (3 days on-site required)
Duration: 1 Year Contract (potential for conversion/extension)
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 Data Engineer will analyze design and develop data products pipelines and information architecture deliverables focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform GitHub and GitHub Actions to deliver scalable reliable and secure data solutions.
Key Responsibilities
Analyze design and develop enterprise data solutions with a focus on Azure Databricks Spark Python and SQL
Develop optimize and maintain Spark/PySpark data pipelines including managing performance issues such as 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 across the enterprise including collaboration with end client when needed
Use Terraform to provision and manage cloud and Databricks resources supporting 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 data pipelines
Apply cloud computing skills to deploy fixes upgrades and enhancements in Azure environments
Work closely 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 the reuse of data assets and contribute to enterprise data catalog practices
Deliver timely and effective support and communication to stakeholders and end users
Mentor team members on data engineering principles best practices and emerging technologies
Requirements
7 years of experience as a Data Engineer
Hands-on experience with Azure Databricks Spark and Python
Experience with Delta Live Tables (DLT) and Databricks SQL
Strong SQL and database background
Experience with Azure Functions messaging services or orchestration tools
Familiarity with data governance lineage or cataloging tools (e.g. Purview Unity Catalog)
Experience monitoring and optimizing Databricks clusters or workflows
Experience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms
Experience with Terraform for cloud infrastructure provisioning
Experience with GitHub and GitHub Actions for version control and CI/CD automation
Strong understanding of distributed computing concepts (partitions joins shuffles cluster behavior)
Familiarity with SDLC and modern engineering practices
Ability to balance multiple priorities work independently and stay organized
Title: Data Engineer Location: Cincinnati OH (3 days on-site required) Duration: 1 Year Contract (potential for conversion/extension) 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-ba...
Title: Data Engineer
Location: Cincinnati OH (3 days on-site required)
Duration: 1 Year Contract (potential for conversion/extension)
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 Data Engineer will analyze design and develop data products pipelines and information architecture deliverables focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform GitHub and GitHub Actions to deliver scalable reliable and secure data solutions.
Key Responsibilities
Analyze design and develop enterprise data solutions with a focus on Azure Databricks Spark Python and SQL
Develop optimize and maintain Spark/PySpark data pipelines including managing performance issues such as 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 across the enterprise including collaboration with end client when needed
Use Terraform to provision and manage cloud and Databricks resources supporting 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 data pipelines
Apply cloud computing skills to deploy fixes upgrades and enhancements in Azure environments
Work closely 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 the reuse of data assets and contribute to enterprise data catalog practices
Deliver timely and effective support and communication to stakeholders and end users
Mentor team members on data engineering principles best practices and emerging technologies
Requirements
7 years of experience as a Data Engineer
Hands-on experience with Azure Databricks Spark and Python
Experience with Delta Live Tables (DLT) and Databricks SQL
Strong SQL and database background
Experience with Azure Functions messaging services or orchestration tools
Familiarity with data governance lineage or cataloging tools (e.g. Purview Unity Catalog)
Experience monitoring and optimizing Databricks clusters or workflows
Experience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms
Experience with Terraform for cloud infrastructure provisioning
Experience with GitHub and GitHub Actions for version control and CI/CD automation
Strong understanding of distributed computing concepts (partitions joins shuffles cluster behavior)
Familiarity with SDLC and modern engineering practices
Ability to balance multiple priorities work independently and stay organized
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