Databricks Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Databricks Lead position based in Cincinnati, OH, on a contract basis. Key skills include Azure Databricks, Apache Spark, ETL processes, and data governance. Experience with Azure SQL migration and optimization is essential. Pay rate is unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
May 21, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Cincinnati, OH
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🧠 - Skills detailed
#SQL Queries #Security #Storage #Indexing #Azure #Azure SQL #"ETL (Extract #Transform #Load)" #Apache Spark #Delta Lake #Databricks #Spark (Apache Spark) #SQL (Structured Query Language) #Data Processing #Azure Databricks #Compliance #Scala #Data Governance #Data Pipeline #Migration
Role description
Job role : Databricks Lead
Location : Cincinnati, OH
Job Type: Contract
Job Description
• Design and implement scalable data pipelines and architectures on Azure Databricks.
• Optimize ETL/ELT workflows, ensuring efficiency in data processing, storage, and retrieval.
• Leverage Apache Spark, Delta Lake, and Azure-native services to build high-performance data solutions.
• Ensure best practices in data governance, security, and compliance within Azure environments.
• Troubleshoot and fine-tune Spark jobs for optimal performance and cost efficiency.
• Lead the migration of Azure SQL to Azure Databricks, ensuring a seamless transition of data workloads.
• Design and implement scalable data pipelines to extract, transform, and load (ETL/ELT) data from Azure SQL into Databricks Delta Lake.
• Optimize Azure SQL queries and indexing strategies before migration to enhance performance in Databricks.
Job role : Databricks Lead
Location : Cincinnati, OH
Job Type: Contract
Job Description
• Design and implement scalable data pipelines and architectures on Azure Databricks.
• Optimize ETL/ELT workflows, ensuring efficiency in data processing, storage, and retrieval.
• Leverage Apache Spark, Delta Lake, and Azure-native services to build high-performance data solutions.
• Ensure best practices in data governance, security, and compliance within Azure environments.
• Troubleshoot and fine-tune Spark jobs for optimal performance and cost efficiency.
• Lead the migration of Azure SQL to Azure Databricks, ensuring a seamless transition of data workloads.
• Design and implement scalable data pipelines to extract, transform, and load (ETL/ELT) data from Azure SQL into Databricks Delta Lake.
• Optimize Azure SQL queries and indexing strategies before migration to enhance performance in Databricks.
