BuzzClan
Databricks Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Databricks Engineer with a contract length of "unknown." The pay rate is "unknown," and it is a remote position. Key skills include Databricks administration, AWS, Apache Spark, IAM, and experience in enterprise environments.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 3, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Austin, TX
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🧠 - Skills detailed
#IAM (Identity and Access Management) #Automation #MLflow #S3 (Amazon Simple Storage Service) #Terraform #Scripting #Databricks #SQL (Structured Query Language) #Data Security #Data Lake #Compliance #Scala #Spark (Apache Spark) #Monitoring #AI (Artificial Intelligence) #ML (Machine Learning) #Security #Apache Spark #Python #AWS (Amazon Web Services) #Cloud #DevOps #Data Governance #Storage
Role description
Experience administering Databricks workspaces in a cloud environment - AWS
Strong understanding of Databricks cluster configuration, job scheduling, and workspace management.
Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC).
Proficiency with Apache Spark concepts, including performance tuning and troubleshooting.
Experience integrating Databricks with cloud storage services (e.g., S3,)
Experience implementing and enforcing cluster policies and workspace governance standards.
Familiarity with Databricks SQL, notebooks, and job orchestration.
Experience monitoring platform health, performance, and availability.
Understanding of data security, encryption, and compliance requirements.
Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting).
Experience administering Databricks in an enterprise or government environment.
Experience with Databricks Unity Catalog for data governance and access control.
Knowledge of cost management and optimization for Databricks workloads.
Experience supporting AI/ML workloads using Databricks ML and MLflow.
Familiarity with data lake and lakehouse architectures.
Knowledge of Python, SQL, or Scala for administration and troubleshooting.
Experience administering Databricks workspaces in a cloud environment - AWS
Strong understanding of Databricks cluster configuration, job scheduling, and workspace management.
Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC).
Proficiency with Apache Spark concepts, including performance tuning and troubleshooting.
Experience integrating Databricks with cloud storage services (e.g., S3,)
Experience implementing and enforcing cluster policies and workspace governance standards.
Familiarity with Databricks SQL, notebooks, and job orchestration.
Experience monitoring platform health, performance, and availability.
Understanding of data security, encryption, and compliance requirements.
Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting).
Experience administering Databricks in an enterprise or government environment.
Experience with Databricks Unity Catalog for data governance and access control.
Knowledge of cost management and optimization for Databricks workloads.
Experience supporting AI/ML workloads using Databricks ML and MLflow.
Familiarity with data lake and lakehouse architectures.
Knowledge of Python, SQL, or Scala for administration and troubleshooting.
