About this role
Company Description
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job Description
Job Description :
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Audit the current Databricks workspace state, including environments, clusters, Unity Catalog setup, access controls, and cost configuration.
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Implement and harden Unity Catalog, including namespace structure, access controls, cluster policies, and environment separation.
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Define workspace standards, naming conventions, access request workflows, and user/team onboarding processes.
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Establish data quality frameworks, including SLAs, certification criteria, and data ownership models.
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Build automation templates for routine workspace operations such as cluster lifecycle management, cost alerting, and utilization monitoring.
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Stand up observability dashboards covering platform health, cost, job success rates, and DQ SLA KPIs, and monitor core data asset lineage across workspaces.
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Create runbooks for recurring operational tasks that can be executed by a mid-level/junior engineer without ongoing support from the senior resource.
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Conduct knowledge-transfer sessions with the platform engineering team.
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Provide final documentation covering architecture decisions, operational standards, open items, and recommendations for the permanent hire profile. Key Responsabilities.
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Evaluate and optimize Databricks environments, including workspaces, clusters, catalogs, permissions, and security configurations.
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Define and implement governance standards to ensure secure, scalable, and compliant platform operations.
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Lead Unity Catalog adoption, designing data structures, access models, and environment segregation strategies.
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Establish RBAC policies, workspace standards, naming conventions, and user access processes.
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Drive data governance initiatives, including data quality frameworks, ownership models, SLAs, lineage, and stewardship practices.
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Develop automation solutions and Infrastructure as Code (IaC) frameworks to streamline platform administration and reduce manual effort.
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Implement cost optimization, monitoring, and operational excellence practices across Databricks environments.
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Design observability and performance dashboards to track platform health, utilization, job success rates, and data quality KPIs.
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Create operational documentation, runbooks, and support procedures to improve platform reliability and team readiness.
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Partner with security, compliance, infrastructure, and data engineering teams to align platform capabilities with business needs.
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Provide training, mentoring, and knowledge transfer sessions to empower platform administrators and engineering teams.
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Recommend platform improvements and long-term strategies to enhance governance, scalability, and organizational maturity.
Qualifications
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Must have skills: Azure Data Factory, Databricks, Unity Catalog
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Good to have skills: Data platform implementation, Google Workspace Administration