What are the responsibilities and job description for the Senior Databricks Platform Engineer position at Masterapp Labs?
Job Title: Senior Databricks Platform Engineer
Location: Austin, TX, (Hybrid)
Position Type: Contract
Interview Mode: In-person
Note: The program will only allow candidates who are LOCAL TO THE AUSTIN AREA ONLY.
Job Description
Understands business objectives and problems, identifies alternative solutions, performs studies and cost/benefit analysis of alternatives. Analyzes user requirements, procedures, and problems to automate processing or to improve existing computer system: Confers with personnel of organizational units involved to analyze current operational procedures, identify problems, and learn specific input and output requirements, such as forms of data input, how data is to be; summarized, and formats for reports. Writes detailed description of user needs, program functions, and steps required to develop or modify computer program. Reviews computer system capabilities, specifications, and scheduling limitations to determine if requested program or program change is possible within existing system.
Additional job details and special considerations
The Databricks Administrator is responsible for administering, configuring, and supporting the Databricks platform to enable scalable data engineering, analytics, and AI/ML workloads. This role ensures platform reliability, security, cost optimization, and compliance while supporting data engineers, analysts, and data scientists across the organization.
The administrator will manage workspace configuration, cluster policies, user access, integrations with cloud services, and ongoing platform monitoring to support enterprise data and analytics initiatives.
II. CANDIDATE SKILLS AND QUALIFICATIONS
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Minimum Requirements:
Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity.
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Years
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Required/Preferred
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Experience
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8
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Required
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Experience administering Databricks workspaces in a cloud environment - AWS
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8
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Required
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Strong understanding of Databricks cluster configuration, job scheduling, and workspace management.
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8
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Required
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Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC).
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8
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Required
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Proficiency with Apache Spark concepts, including performance tuning and troubleshooting.
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8
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Required
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Experience integrating Databricks with cloud storage services (e.g., S3,)
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8
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Required
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Experience implementing and enforcing cluster policies and workspace governance standards.
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8
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Required
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Familiarity with Databricks SQL, notebooks, and job orchestration.
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8
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Required
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Experience monitoring platform health, performance, and availability.
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8
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Required
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Understanding of data security, encryption, and compliance requirements.
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8
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Required
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Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting).
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4
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Preferred
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Experience administering Databricks in an enterprise or government environment.
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4
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Preferred
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Experience with Databricks Unity Catalog for data governance and access control.
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4
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Preferred
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Knowledge of cost management and optimization for Databricks workloads.
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4
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Preferred
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Experience supporting AI/ML workloads using Databricks ML and MLflow.
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4
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Preferred
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Familiarity with data lake and lakehouse architectures.
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4
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Preferred
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Knowledge of Python, SQL, or Scala for administration and troubleshooting.
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