Intellisoft Technologies
AWS Databricks Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Databricks Engineer in Malvern, PA, with a contract length of unspecified duration and a pay rate of "C2C okay." Key skills include AWS, Databricks, Terraform, and Data Engineering, requiring senior-level expertise in cloud architecture and data pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 1, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Corp-to-Corp (C2C)
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🔒 - Security
Unknown
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📍 - Location detailed
Malvern, PA
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🧠 - Skills detailed
#PySpark #Data Pipeline #DevOps #Spark (Apache Spark) #Cloud #Databricks #Data Engineering #Monitoring #Terraform #Scala #AWS (Amazon Web Services)
Role description
Role: AWS Databricks Engineer
Location: Malvern, PA
C2C is okay
This role is best suited for a senior-level engineer who combines strong AWS Infrastructure expertise with hands-on Databricks administration and modern Data Engineering experience.
Must have:
• We are looking for an engineer who can:
• Build AWS infrastructure from scratch using Terraform
• Set up and administer Databricks environments
• Design secure cloud architectures and networking
• Implement CI/CD and DevOps best practices
• Develop scalable Spark/PySpark data pipelines
• Optimize AWS and Databricks costs
• Own platform reliability, monitoring, and governance
• Work independently across Cloud, DevOps, and Data Engineering functions
Role: AWS Databricks Engineer
Location: Malvern, PA
C2C is okay
This role is best suited for a senior-level engineer who combines strong AWS Infrastructure expertise with hands-on Databricks administration and modern Data Engineering experience.
Must have:
• We are looking for an engineer who can:
• Build AWS infrastructure from scratch using Terraform
• Set up and administer Databricks environments
• Design secure cloud architectures and networking
• Implement CI/CD and DevOps best practices
• Develop scalable Spark/PySpark data pipelines
• Optimize AWS and Databricks costs
• Own platform reliability, monitoring, and governance
• Work independently across Cloud, DevOps, and Data Engineering functions
