Manager – Engineering

Location: 100% remote

Responsibilities

• 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

• Coordinate AIDF engineering priorities and resource allocation

• Manage GTM KG Engineering workload and strategy - working directly with JS and team

• Partner with PMM team for drafting table rollout

• Partner with CX Coworker pod for AIDF scoping

• Partner with Analyst / Intl DE org for QUBE rollout and strategy + AIDF MCP UAT

• Partner with ATS/DPAAS on Databricks administration and VOC

• Coordinate with marketing data owners and source-system teams

• Translate business requirements into engineering scope

• Escalate capacity, architecture, timeline and delivery risks

• Document key decisions for post-leave transition