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# Data Engineer

- **Company:** Proteam Solutions
- **Location:** Dublin, OH, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Application Frameworks, Microsoft Azure, Computer Programming, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Distributed Data Store, Apache Hive, Performance Tuning, Data Streaming, Delivery Pipeline, Apache Spark, Git, Data Layers, Build Management, Data Lakes, Pyspark, Integration Frameworks, Data Pipelines, Databricks
- **Published:** July 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f8246db3d6b3a10d

## About the Role

* 7-10+ years of Data Engineering experience
 * Extensive hands-on Databricks experience
 * Strong PySpark programming
 * Advanced Spark SQL skills
 * Experience with Delta Lake
 * Experience implementing Medallion Architecture
 * Hands-on Delta Live Tables
 * Unity Catalog experience
 * Strong SQL optimization and performance tuning
 * Experience with AWS, Azure, or GCP
 * CI/CD and Git experience
 * Strong understanding of distributed data systems
 * Experience designing enterprise data models, * Databricks certification
 * Experience with streaming data
 * Experience building reusable data frameworks
 * Experience with enterprise governance
 * Exposure to AI-assisted development tools including Databricks AI Genie

## Description

We are seeking an experienced Senior Data Engineer with deep expertise in Databricks to design, develop, and optimize enterprise-scale data pipelines. You'll play a key role in building scalable Lakehouse solutions while ensuring reliable, high-quality data for analytics, reporting, and downstream applications., * Design and build scalable ETL/ELT pipelines using Databricks

 * Develop PySpark and Spark SQL transformations
 * Build Bronze, Silver, and Gold data layers using Medallion Architecture
 * Implement Delta Live Tables, Workflows, and Unity Catalog
 * Optimize Spark jobs for scalability and performance
 * Design dimensional data models for analytical workloads
 * Implement data quality validations and monitoring
 * Collaborate with analytics, engineering, and architecture teams
 * Build reusable frameworks and automation
 * Support CI/CD deployment pipelines and Git-based development


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