Role : Databricks Engineering Manager
Duration : 6+ Months
Location : Remote
Job Description :
-Manage AIDF priorities, backlog, blockers, UAT and delivery risks
-Review and approve pull requests on demand
-Administer Databricks access, permissions and personal clusters
Serve as primary contact for ATS/DPAAS Databricks administrators -Direct GTM KG engineering delivery and dependencies
Continue Coworker integration and architecture scoping
-Direct Eng resources / strategy Voice of Customer migration
-Lead stakeholder and management level touch points for all the above
Skills required:
Databricks: catalogs, schemas, tables, jobs, clusters, serverless, AI capabilities, IAM, pipelines and repos
SQL, Python, PySpark and REST APIs
-Front-end and back-end application development
-Data architecture, sourcing, transformations and pipeline design
-Knowledge graphs, MCP, Agent Builder and agent workflows
-Pull request review and engineering oversight
Domain knowledge:
"-AIDF architecture, roadmap and operating model -GTM Knowledge Graph ingestion, serving and use cases -Coworker context, integration and orchestration patterns -Marketing data: campaign, paid media, web, email and CRM -Marketing KPIs: impressions, CTR, conversions, MQL/SQL and pipeline attribution -AEP data models and schema conventions -Adobe Analytics and Adobe Target data structures -Marketo, Dynamics, Salesforce, Third Party Vendor integrations -Data governance, PII, GDPR and CCPA requirements -Data partners, issue mitigation, lineage and transformation flows"
Required access/Platforms used:
"-Databricks and associated administrative access -Jira and source-control repositories -AIDF and MCP environments -Agent Builder, GTM STudio, BrAIns -Github -GH Copilot -Azure Portal -Workfront Planning -AEP, Adobe Analytics and Adobe Target -Marketo and Salesforce -Teams, SharePoint and UAT tracking tools"
Stakeholder engagement & Cross team alignment:
